Dr. Book - Linking a Book to Open Data Sources

Abstract:

For any text-based resource, we will attempt to extract named entities, such as people, places, topics and concepts, to render an annotated version of the text, linking the text to Open Data resources. Our tool parses books authored using the Docbook XML structure (http://docbook.org/tdg51/en/html/) and also uses natural language processing techniques to process raw text, attempting to extract terms which can be linked to wikipedia and other Open Data resources. Our tool is potentially useful for pre and post processing a text document. Pre-processing would take place during the authoring and publication process to create supplementatal resources for inclusion in the text. Post-processing would take place at reading time in the form of a browser or ereader extension which annotates the text of the page.

Original Idea:

Two of our team members are involved in the Future of eBooks seminar in which students have created an open-source eBook reader. We believe that books should be platform-independent and plugin-extensible.

Our team decided to work on a project that would explore the use of Open Data to augment the reading experience by adding semantic web-like links to connect information within a book to the Web.

Project code can be found on github here: https://github.com/AJRenold/doctorbook

In [2]:
#imports
from bs4 import BeautifulSoup, NavigableString, Tag
import nltk
import pandas as pd
import re
from itertools import islice
from collections import Counter
import os

# Our tools
from get_wiki_links import WikiUrlFetch, WikiUrlFetchNonDBPedia
from get_wiki_text import Wiki2Plain

TDO: The Discipline of Organizing:

The team chose Prof. Glushko's upcoming textbook The Discipline of Organizing (TDO) to use to develop ideas for our project. We thought the book would be a good test case for the project, as it is authored in DocBook XML, with structured markup of entities within the text, and many references to entities with wikipedia entries. This allowed us to work on XML and raw text parsing.

Read Chapter1.xml into BeautifulSoup

In [3]:
PATH = 'Chapter1.xml'
soup = BeautifulSoup(open(PATH, 'rt').read())

Picking up tags:

TDO uses the DocBook XML markup standard, providing a solid base for analyzing terms by parsing specific tags in the text.

After exploring the text, we opted to use the tags "keyword," "author," "indexterm," "orgname," "personname," and "phrase."

Which tags are in the soup?

In [4]:
book_tags = set([tag.name for tag in soup.findAll(True)])
print(book_tags)
set(['ulink', 'surname', 'figure', 'footnote', 'othername', 'primary', 'uri', 'hardware', 'citerefentry', 'manvolnum', 'phrase', 'sidebar', 'tertiary', 'xref', 'sect2', 'para', 'sect1', 'orgname', 'highlights', 'sect1info', 'abbrev', 'filename', 'application', 'emphasis', 'html', 'listitem', 'textobject', 'indexterm', 'chapterinfo', 'firstterm', 'body', 'keywordset', 'blockquote', 'attribution', 'firstname', 'quote', 'symbol', 'literal', 'sect3info', 'citetitle', 'link', 'foreignphrase', 'secondary', 'chapter', 'mediaobject', 'sidebarinfo', 'imagedata', 'keyword', 'glossterm', 'author', 'imageobject', 'personname', 'sect2info', 'refentrytitle', 'action', 'title', 'itemizedlist', 'sect3'])

Using selected tags to construct a Pandas DataFrame with terms from the text

In [5]:
# The following script looks for terms within select tags and creates a Pandas DataFrame object.
# The DataFrame consists of "count" (term counter), "tag" (the XML tag for which the term is an attribute),
# and "term" (the term found within the tag).

list_for_df = []
tags = ['keyword','author','indexterm','orgname','personname','phrase']
for tag in tags:
    for i in soup.findAll(tag):
        if i.string == None:
            list_for_df.append({ 'term':" ".join([ child.lower().encode('utf-8') for child in i.stripped_strings ]), \
                                'tag': tag, 'count': 1 })
        else:
            list_for_df.append({ 'term': re.sub('  +','', i.string.lower().encode('utf-8')), 'tag': tag, 'count': 1 })
        
book_df = pd.DataFrame(list_for_df)
In [6]:
# First 10 entries of the DataFrame.
book_df[0:10]
Out[6]:
count tag term
0 1 keyword organize
1 1 keyword organizing system
2 1 keyword discipline
3 1 keyword framework
4 1 keyword resource
5 1 keyword collection
6 1 keyword intentional arrangement
7 1 keyword agent
8 1 keyword description resource
9 1 keyword primary resource

Text Processing with nltk to find Named Entities in the Text

Regex v. Natural Language Processing:

Our team explored both Regex-based, and Natural Language-based entity recognition techniques. We initially worked with Regex, thinking it would provide a more flexible, rule-based method of identifying terms with less overhead. We quickly realized that Natural Language Processing offers a better solution to our problem. As the old hacker adage goes: don't reinvent the wheel!

We used NLTK, a Python module rich in natural language tools, to tag words by part of speech. We then focused on parts of speech which could be mapped to named entities, nouns and proper nouns.

Here's the script for cleaning up the text and tagging each word.

In [7]:
# We used NLTK (Natural Language Toolkit) to identify terms within the text that are not markedup
# with XML.

# First we create one large text by stripping the markup from XML.
all_xml =  " ".join([ line for line in soup.stripped_strings])
text = nltk.clean_html(all_xml)

# We then clean the text through string subsitutions.
text = re.sub(r"[\n\.,\(\)\?\!\-':]","",text)

# Finally, we use nltk.pos_tag to insert part-of-speech tags to each word in the text.
tagged_text = nltk.pos_tag(text.split(' '))

Noun Chains

To create a list of potentially named entities in the document, we looked for nouns and variations of nouns (singlar v. plural, general nouns v. proper nouns). We then developed an algorithm to create chains of nouns that appear next to each other. The hypothesis for this is that two or more nouns appearing next to each other likely name the same entity, such as Berkeley California, Nunberg Geoff, or library information systems

In [8]:
pos = ['NN','NNS','NNP','NNPS'] ## nltk noun tags

terms = []
chain = []
for term in tagged_text: ## loop through tagged text (in its original order)
    
    if term[1] in pos: ## if a term is in our pos list, append the term to the chain and to the noun list
        chain.append(term)
        terms.append(term[0].lower().encode('UTF-8'))
        terms.append(" ".join([ item[0].lower().encode('UTF-8') for item in chain ]))
        
    else: ## at the end of a sequence of nouns, append the chain to the noun list and reset the chain
        if len(chain) > 0:
            terms.append(" ".join([ item[0].lower().encode('UTF-8') for item in chain ]))
            chain = []
            
terms = [ re.sub(' +',' ',term) for term in terms if term != '' ] # clean extra spaces from noun chains
terms = [ re.sub('^ ','',term) for term in terms ] 
In [9]:
## sample of terms scrapped
print terms[100:130]
['order', 'order', 'order', '', '', '', 'structure', 'structure', 'organizing', 'structure organizing', 'structure organizing', 'activity', 'activity', 'activity', 'shoes', 'shoes', 'shoes', 'closet', 'closet', 'closet', '', 'books', 'books', 'books', 'book', 'book', 'shelves', 'book shelves', 'book shelves', 'spices']

Append new terms to DataFrame

As an approach to processing named entities from a large document, we choose to filter terms that occurred less than a certain number of times. We settled for 2 since setting it higher would have excluded many terms crucial to the understanding of a text. The issue here is that this method, while retaining precision, had very high recall.

In [10]:
terms_for_df = []
term_count = Counter(terms)

# count_threshold should be a number that returns a good amount of information within a reasonable amount of time.
# This depends on what the reader is looking for, and how much computational power they have.
# Theoretically speaking, it could be 0 if a reader wants to see all terms, and can process that amount of data on their computer.
count_threshold = 2

for term,count in term_count.iteritems():
    if count >= count_threshold:
        terms_for_df.append({ 'term': term,'count': count })
        #print term, count
In [11]:
# check state of original book_df (366 terms)
book_df
Out[11]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 366 entries, 0 to 365
Data columns:
count    366  non-null values
tag      366  non-null values
term     366  non-null values
dtypes: int64(1), object(2)
In [12]:
## create list of dict for appending to df
list_for_df = []
for item in terms_for_df:
    if item['term'] != "" and item['term'] != " ":
        list_for_df.append({ 'term': item['term'], 'count': item['count'], 'tag': 'raw'})

Append terms scrapped from text to book_df

In [13]:
book_df = book_df.append(pd.DataFrame(list_for_df))
In [14]:
## check the raw terms that were appended
df_rawterms = book_df[book_df['tag']=='raw']
In [15]:
df_rawterms
Out[15]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2863 entries, 0 to 2862
Data columns:
count    2863  non-null values
tag      2863  non-null values
term     2863  non-null values
dtypes: int64(1), object(2)
In [16]:
# check state of new book_df (3229 terms)
book_df
Out[16]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3229 entries, 0 to 2862
Data columns:
count    3229  non-null values
tag      3229  non-null values
term     3229  non-null values
dtypes: int64(1), object(2)
In [17]:
## drop duplicated terms
book_df.drop_duplicates()
Out[17]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3190 entries, 0 to 2862
Data columns:
count    3190  non-null values
tag      3190  non-null values
term     3190  non-null values
dtypes: int64(1), object(2)

Connecting to the web with DBPedia and Wikipedia:

Our team decided to connect all identified named entities to Wikipedia using a DBpedia Look-up API and DBPedia entity pages. We used an edit distance method to judge the quality of matched entities when the match was not exact. Matches are rated as being "exact" (exact match), "good-partial" (a likely useful partial match), "partial" (dubious match) and "none". The match ratings are stored in the DataFrame. After completing the code for this tool, we encapulated the tool in the class WikiUrlFetch, so that it could be easily reusable. This class is available in the appendix of this notebook and on github

This method for matching text terms to Wikipedia entries created two of the main challenges of our project

  1. Time dependence on 3rd party APIs - as we worked on mapping named entities to wikipedia urls and expanded our tool from searching for a few terms to searching for thousands of terms, we realized that the response time of the DBPedia APIs was hindering the performance of our tool. For example matching the 3,000+ terms in a single chapter took upwards of three hours.
  2. Evaluating match quality - it is a challenge to judge the semantic quality of matches, therefore even good-partial matches do not aways have the same semantic meaning as the term searched

*As an attempted solution to the slow response time from DBPedia, we expermented with another Wikipedia Lookup API. This is shown in the class WikiUrlFetchNonDBPedia in the appendix and on Github.

In [71]:
from get_wiki_links import WikiUrlFetch, WikiUrlFetchNonDBPedia
In [18]:
## example query with WikiUrlFetch
w = WikiUrlFetch()
print w.fetch_wiki("Nunberg Geoff")
[{'url': 'http://dbpedia.org/resource/Geoffrey_Nunberg', 'term': 'geoffrey nunberg', 'wiki_url': 'http://en.wikipedia.org/wiki/Geoffrey_Nunberg', 'match': 'good-partial'}]

Using WikiUrlFetch, look up wikipedia URLs for terms in the text

In [19]:
from itertools import islice
import time

list_for_wiki_df = []
w = WikiUrlFetch()

for row in islice(book_df.iterrows(),1000): # iterations limited 100 because WikiUrlFetch because of API limitations

    wikis = w.fetch_wiki(row[1]['term'])
    
    for wiki in wikis:
        print wiki
        if wiki['match'] == 'exact' or wiki['match'] == 'good-partial' or wiki['match'] == 'partial':
            list_for_wiki_df.append( { 'term': row[1]['term'], 'matched_term': wiki['term'], \
            'count': row[1]['count'], 'match': wiki['match'], 'url': wiki['wiki_url'] } )
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Taboo', 'term': 'taboo', 'wiki_url': 'http://en.wikipedia.org/wiki/Taboo', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Monasticism', 'term': 'monasticism', 'wiki_url': 'http://en.wikipedia.org/wiki/Monasticism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Assault', 'term': 'assault', 'wiki_url': 'http://en.wikipedia.org/wiki/Assault', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Homicide', 'term': 'homicide', 'wiki_url': 'http://en.wikipedia.org/wiki/Homicide', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Type_(biology)', 'term': 'type (biology)', 'wiki_url': 'http://en.wikipedia.org/wiki/Type_(biology)', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Binomial_nomenclature', 'term': 'binomial nomenclature', 'wiki_url': 'http://en.wikipedia.org/wiki/Binomial_nomenclature', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Metadata', 'term': 'metadata', 'wiki_url': 'http://en.wikipedia.org/wiki/Metadata', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Charles_Darwin', 'term': 'charles darwin', 'wiki_url': 'http://en.wikipedia.org/wiki/Charles_Darwin', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Robert_E._Lee', 'term': 'robert e. lee', 'wiki_url': 'http://en.wikipedia.org/wiki/Robert_E._Lee', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Greatest_hits_album', 'term': 'greatest hits album', 'wiki_url': 'http://en.wikipedia.org/wiki/Greatest_hits_album', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Toll_road', 'term': 'toll road', 'wiki_url': 'http://en.wikipedia.org/wiki/Toll_road', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Assault', 'term': 'assault', 'wiki_url': 'http://en.wikipedia.org/wiki/Assault', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Homicide', 'term': 'homicide', 'wiki_url': 'http://en.wikipedia.org/wiki/Homicide', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Extended_play', 'term': 'extended play', 'wiki_url': 'http://en.wikipedia.org/wiki/Extended_play', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer', 'term': 'computer', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Terrorism', 'term': 'terrorism', 'wiki_url': 'http://en.wikipedia.org/wiki/Terrorism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Sport', 'term': 'sport', 'wiki_url': 'http://en.wikipedia.org/wiki/Sport', 'match': 'partial'}
{'term': 'partwhole inclusion', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Subset', 'term': 'subset', 'wiki_url': 'http://en.wikipedia.org/wiki/Subset', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Social', 'term': 'social', 'wiki_url': 'http://en.wikipedia.org/wiki/Social', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Extended_play', 'term': 'extended play', 'wiki_url': 'http://en.wikipedia.org/wiki/Extended_play', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer', 'term': 'computer', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Information_technology', 'term': 'information technology', 'wiki_url': 'http://en.wikipedia.org/wiki/Information_technology', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Statistics', 'term': 'statistics', 'wiki_url': 'http://en.wikipedia.org/wiki/Statistics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Geoffrey_Nunberg', 'term': 'geoffrey nunberg', 'wiki_url': 'http://en.wikipedia.org/wiki/Geoffrey_Nunberg', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Concept_album', 'term': 'concept album', 'wiki_url': 'http://en.wikipedia.org/wiki/Concept_album', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Social_network', 'term': 'social network', 'wiki_url': 'http://en.wikipedia.org/wiki/Social_network', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Zoo', 'term': 'zoo', 'wiki_url': 'http://en.wikipedia.org/wiki/Zoo', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Hoboken,_New_Jersey', 'term': 'hoboken, new jersey', 'wiki_url': 'http://en.wikipedia.org/wiki/Hoboken%2C_New_Jersey', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library', 'term': 'library', 'wiki_url': 'http://en.wikipedia.org/wiki/Library', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library_of_Congress', 'term': 'library of congress', 'wiki_url': 'http://en.wikipedia.org/wiki/Library_of_Congress', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library', 'term': 'library', 'wiki_url': 'http://en.wikipedia.org/wiki/Library', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library_of_Congress', 'term': 'library of congress', 'wiki_url': 'http://en.wikipedia.org/wiki/Library_of_Congress', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Moby', 'term': 'moby', 'wiki_url': 'http://en.wikipedia.org/wiki/Moby', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Herman_Melville', 'term': 'herman melville', 'wiki_url': 'http://en.wikipedia.org/wiki/Herman_Melville', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Moby', 'term': 'moby', 'wiki_url': 'http://en.wikipedia.org/wiki/Moby', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Herman_Melville', 'term': 'herman melville', 'wiki_url': 'http://en.wikipedia.org/wiki/Herman_Melville', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Race_and_ethnicity_in_the_United_States_Census', 'term': 'race and ethnicity in the united states census', 'wiki_url': 'http://en.wikipedia.org/wiki/Race_and_ethnicity_in_the_United_States_Census', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/White_House', 'term': 'white house', 'wiki_url': 'http://en.wikipedia.org/wiki/White_House', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Taboo', 'term': 'taboo', 'wiki_url': 'http://en.wikipedia.org/wiki/Taboo', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Monasticism', 'term': 'monasticism', 'wiki_url': 'http://en.wikipedia.org/wiki/Monasticism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Taboo', 'term': 'taboo', 'wiki_url': 'http://en.wikipedia.org/wiki/Taboo', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Monasticism', 'term': 'monasticism', 'wiki_url': 'http://en.wikipedia.org/wiki/Monasticism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library', 'term': 'library', 'wiki_url': 'http://en.wikipedia.org/wiki/Library', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Library_of_Congress', 'term': 'library of congress', 'wiki_url': 'http://en.wikipedia.org/wiki/Library_of_Congress', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Concept_album', 'term': 'concept album', 'wiki_url': 'http://en.wikipedia.org/wiki/Concept_album', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Social_network', 'term': 'social network', 'wiki_url': 'http://en.wikipedia.org/wiki/Social_network', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computing', 'term': 'computing', 'wiki_url': 'http://en.wikipedia.org/wiki/Computing', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Supercomputer', 'term': 'supercomputer', 'wiki_url': 'http://en.wikipedia.org/wiki/Supercomputer', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Cataloging', 'term': 'cataloging', 'wiki_url': 'http://en.wikipedia.org/wiki/Cataloging', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Trade-off', 'term': 'trade-off', 'wiki_url': 'http://en.wikipedia.org/wiki/Trade-off', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Space\xe2\x80\x93time_tradeoff', 'term': 'space\xe2\x80\x93time tradeoff', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Database', 'term': 'database', 'wiki_url': 'http://en.wikipedia.org/wiki/Database', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Special_relativity', 'term': 'special relativity', 'wiki_url': 'http://en.wikipedia.org/wiki/Special_relativity', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Trade-off', 'term': 'trade-off', 'wiki_url': 'http://en.wikipedia.org/wiki/Trade-off', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Space\xe2\x80\x93time_tradeoff', 'term': 'space\xe2\x80\x93time tradeoff', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Primary_school', 'term': 'primary school', 'wiki_url': 'http://en.wikipedia.org/wiki/Primary_school', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Primary_sector_of_the_economy', 'term': 'primary sector of the economy', 'wiki_url': 'http://en.wikipedia.org/wiki/Primary_sector_of_the_economy', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Concept_album', 'term': 'concept album', 'wiki_url': 'http://en.wikipedia.org/wiki/Concept_album', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Social_network', 'term': 'social network', 'wiki_url': 'http://en.wikipedia.org/wiki/Social_network', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Hypertext_Transfer_Protocol', 'term': 'hypertext transfer protocol', 'wiki_url': 'http://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Conservatoire_de_Paris', 'term': 'conservatoire de paris', 'wiki_url': 'http://en.wikipedia.org/wiki/Conservatoire_de_Paris', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/RAI', 'term': 'rai', 'wiki_url': 'http://en.wikipedia.org/wiki/RAI', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Hypertext_Transfer_Protocol', 'term': 'hypertext transfer protocol', 'wiki_url': 'http://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Conservatoire_de_Paris', 'term': 'conservatoire de paris', 'wiki_url': 'http://en.wikipedia.org/wiki/Conservatoire_de_Paris', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/RAI', 'term': 'rai', 'wiki_url': 'http://en.wikipedia.org/wiki/RAI', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Hypertext_Transfer_Protocol', 'term': 'hypertext transfer protocol', 'wiki_url': 'http://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Conservatoire_de_Paris', 'term': 'conservatoire de paris', 'wiki_url': 'http://en.wikipedia.org/wiki/Conservatoire_de_Paris', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer_science', 'term': 'computer science', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer_science', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer', 'term': 'computer', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer', 'match': 'partial'}
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{'url': 'http://dbpedia.org/resource/Governor-General', 'term': 'governor-general', 'wiki_url': 'http://en.wikipedia.org/wiki/Governor-General', 'match': 'partial'}
{'url': "http://dbpedia.org/resource/Tim_O'Reilly", 'term': "tim o'reilly", 'wiki_url': "http://en.wikipedia.org/wiki/Tim_O'Reilly", 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Flipper_(band)', 'term': 'flipper (band)', 'wiki_url': 'http://en.wikipedia.org/wiki/Flipper_(band)', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Iraq_Veterans_Against_the_War', 'term': 'iraq veterans against the war', 'wiki_url': 'http://en.wikipedia.org/wiki/Iraq_Veterans_Against_the_War', 'match': 'partial'}
{'term': 'amazoncom', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/EBay', 'term': 'ebay', 'wiki_url': 'http://en.wikipedia.org/wiki/EBay', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Twitter', 'term': 'twitter', 'wiki_url': 'http://en.wikipedia.org/wiki/Twitter', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Facebook', 'term': 'facebook', 'wiki_url': 'http://en.wikipedia.org/wiki/Facebook', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Folksonomy', 'term': 'folksonomy', 'wiki_url': 'http://en.wikipedia.org/wiki/Folksonomy', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Computer_science', 'term': 'computer science', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer_science', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer', 'term': 'computer', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Yahoo!', 'term': 'yahoo!', 'wiki_url': 'http://en.wikipedia.org/wiki/Yahoo!', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Trade-off', 'term': 'trade-off', 'wiki_url': 'http://en.wikipedia.org/wiki/Trade-off', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Space\xe2\x80\x93time_tradeoff', 'term': 'space\xe2\x80\x93time tradeoff', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Neural_network', 'term': 'neural network', 'wiki_url': 'http://en.wikipedia.org/wiki/Neural_network', 'match': 'partial'}
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{'url': 'http://dbpedia.org/resource/Taxonomic_rank', 'term': 'taxonomic rank', 'wiki_url': 'http://en.wikipedia.org/wiki/Taxonomic_rank', 'match': 'partial'}
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{'url': 'http://dbpedia.org/resource/Harvard_University', 'term': 'harvard university', 'wiki_url': 'http://en.wikipedia.org/wiki/Harvard_University', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/University_of_Oxford', 'term': 'university of oxford', 'wiki_url': 'http://en.wikipedia.org/wiki/University_of_Oxford', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/High_school', 'term': 'high school', 'wiki_url': 'http://en.wikipedia.org/wiki/High_school', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/State_school', 'term': 'state school', 'wiki_url': 'http://en.wikipedia.org/wiki/State_school', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/University_of_California,_Berkeley', 'term': 'university of california, berkeley', 'wiki_url': 'http://en.wikipedia.org/wiki/University_of_California%2C_Berkeley', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Berkeley,_California', 'term': 'berkeley, california', 'wiki_url': 'http://en.wikipedia.org/wiki/Berkeley%2C_California', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/World_War_II', 'term': 'world war ii', 'wiki_url': 'http://en.wikipedia.org/wiki/World_War_II', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/World_War_I', 'term': 'world war i', 'wiki_url': 'http://en.wikipedia.org/wiki/World_War_I', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States', 'term': 'united states', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States_Census_Bureau', 'term': 'united states census bureau', 'wiki_url': 'http://en.wikipedia.org/wiki/United_States_Census_Bureau', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/England_national_football_team', 'term': 'england national football team', 'wiki_url': 'http://en.wikipedia.org/wiki/England_national_football_team', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/American_Hockey_League', 'term': 'american hockey league', 'wiki_url': 'http://en.wikipedia.org/wiki/American_Hockey_League', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/England_national_football_team', 'term': 'england national football team', 'wiki_url': 'http://en.wikipedia.org/wiki/England_national_football_team', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/American_Hockey_League', 'term': 'american hockey league', 'wiki_url': 'http://en.wikipedia.org/wiki/American_Hockey_League', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Flickr', 'term': 'flickr', 'wiki_url': 'http://en.wikipedia.org/wiki/Flickr', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/United_States', 'term': 'united states', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States_Census_Bureau', 'term': 'united states census bureau', 'wiki_url': 'http://en.wikipedia.org/wiki/United_States_Census_Bureau', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States', 'term': 'united states', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States_Census_Bureau', 'term': 'united states census bureau', 'wiki_url': 'http://en.wikipedia.org/wiki/United_States_Census_Bureau', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Alfred_Hitchcock', 'term': 'alfred hitchcock', 'wiki_url': 'http://en.wikipedia.org/wiki/Alfred_Hitchcock', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Henry_Kissinger', 'term': 'henry kissinger', 'wiki_url': 'http://en.wikipedia.org/wiki/Henry_Kissinger', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Extended_play', 'term': 'extended play', 'wiki_url': 'http://en.wikipedia.org/wiki/Extended_play', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer', 'term': 'computer', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States', 'term': 'united states', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/United_States_Census_Bureau', 'term': 'united states census bureau', 'wiki_url': 'http://en.wikipedia.org/wiki/United_States_Census_Bureau', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Habitat', 'term': 'habitat', 'wiki_url': 'http://en.wikipedia.org/wiki/Habitat', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Horror_film', 'term': 'horror film', 'wiki_url': 'http://en.wikipedia.org/wiki/Horror_film', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/SeaWorld', 'term': 'seaworld', 'wiki_url': 'http://en.wikipedia.org/wiki/SeaWorld', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Harvard_University', 'term': 'harvard university', 'wiki_url': 'http://en.wikipedia.org/wiki/Harvard_University', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/University_of_Oxford', 'term': 'university of oxford', 'wiki_url': 'http://en.wikipedia.org/wiki/University_of_Oxford', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Flickr', 'term': 'flickr', 'wiki_url': 'http://en.wikipedia.org/wiki/Flickr', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Westlaw', 'term': 'westlaw', 'wiki_url': 'http://en.wikipedia.org/wiki/Westlaw', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/LexisNexis', 'term': 'lexisnexis', 'wiki_url': 'http://en.wikipedia.org/wiki/LexisNexis', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/National_Register_of_Historic_Places', 'term': 'national register of historic places', 'wiki_url': 'http://en.wikipedia.org/wiki/National_Register_of_Historic_Places', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/National_Football_League', 'term': 'national football league', 'wiki_url': 'http://en.wikipedia.org/wiki/National_Football_League', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'term': 'amazoncom', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/EBay', 'term': 'ebay', 'wiki_url': 'http://en.wikipedia.org/wiki/EBay', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Wikipedia', 'term': 'wikipedia', 'wiki_url': 'http://en.wikipedia.org/wiki/Wikipedia', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Facebook', 'term': 'facebook', 'wiki_url': 'http://en.wikipedia.org/wiki/Facebook', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Twitter', 'term': 'twitter', 'wiki_url': 'http://en.wikipedia.org/wiki/Twitter', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/YouTube', 'term': 'youtube', 'wiki_url': 'http://en.wikipedia.org/wiki/YouTube', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Microsoft', 'term': 'microsoft', 'wiki_url': 'http://en.wikipedia.org/wiki/Microsoft', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Yahoo!', 'term': 'yahoo!', 'wiki_url': 'http://en.wikipedia.org/wiki/Yahoo!', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Google', 'term': 'google', 'wiki_url': 'http://en.wikipedia.org/wiki/Google', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Microsoft', 'term': 'microsoft', 'wiki_url': 'http://en.wikipedia.org/wiki/Microsoft', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Herman_Melville', 'term': 'herman melville', 'wiki_url': 'http://en.wikipedia.org/wiki/Herman_Melville', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Adam_Smith', 'term': 'adam smith', 'wiki_url': 'http://en.wikipedia.org/wiki/Adam_Smith', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Charles_Darwin', 'term': 'charles darwin', 'wiki_url': 'http://en.wikipedia.org/wiki/Charles_Darwin', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Queen_Anne_style_architecture', 'term': 'queen anne style architecture', 'wiki_url': 'http://en.wikipedia.org/wiki/Queen_Anne_style_architecture', 'match': 'partial'}
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{'url': 'http://dbpedia.org/resource/Miss_World', 'term': 'miss world', 'wiki_url': 'http://en.wikipedia.org/wiki/Miss_World', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Pula', 'term': 'pula', 'wiki_url': 'http://en.wikipedia.org/wiki/Pula', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Thomas_Jefferson', 'term': 'thomas jefferson', 'wiki_url': 'http://en.wikipedia.org/wiki/Thomas_Jefferson', 'match': 'partial'}
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{'term': 'to organize is to create capabilities by intentionally imposing order and                    structure', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Information_technology', 'term': 'information technology', 'wiki_url': 'http://en.wikipedia.org/wiki/Information_technology', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Statistics', 'term': 'statistics', 'wiki_url': 'http://en.wikipedia.org/wiki/Statistics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Cognition', 'term': 'cognition', 'wiki_url': 'http://en.wikipedia.org/wiki/Cognition', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Dementia', 'term': 'dementia', 'wiki_url': 'http://en.wikipedia.org/wiki/Dementia', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/State_school', 'term': 'state school', 'wiki_url': 'http://en.wikipedia.org/wiki/State_school', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Religion', 'term': 'religion', 'wiki_url': 'http://en.wikipedia.org/wiki/Religion', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Computer_science', 'term': 'computer science', 'wiki_url': 'http://en.wikipedia.org/wiki/Computer_science', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Information_technology', 'term': 'information technology', 'wiki_url': 'http://en.wikipedia.org/wiki/Information_technology', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Statistics', 'term': 'statistics', 'wiki_url': 'http://en.wikipedia.org/wiki/Statistics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Baroque', 'term': 'baroque', 'wiki_url': 'http://en.wikipedia.org/wiki/Baroque', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Classical_music', 'term': 'classical music', 'wiki_url': 'http://en.wikipedia.org/wiki/Classical_music', 'match': 'partial'}
{'term': 'a discipline is an integrated field of study in which there is some level of agreement about                    the issues and problems that deserve study how they are interrelated how they                    should be studied and how findings or theories about the issues and problems                    should be evaluated', 'match': 'none'}
{'term': 'a framework is a set of concepts that provide the basic structure for understanding a                    domain enabling a common vocabulary for different explanatory                    theories', 'match': 'none'}
{'term': 'an organizing system is a collection of resources arranged in ways thatenable people or computational agents to interact with them', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Radio-frequency_identification', 'term': 'radio-frequency identification', 'wiki_url': 'http://en.wikipedia.org/wiki/Radio-frequency_identification', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Standardization', 'term': 'standardization', 'wiki_url': 'http://en.wikipedia.org/wiki/Standardization', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Polygamy', 'term': 'polygamy', 'wiki_url': 'http://en.wikipedia.org/wiki/Polygamy', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Loanword', 'term': 'loanword', 'wiki_url': 'http://en.wikipedia.org/wiki/Loanword', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/International_Union_for_Conservation_of_Nature', 'term': 'international union for conservation of nature', 'wiki_url': 'http://en.wikipedia.org/wiki/International_Union_for_Conservation_of_Nature', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Renewable_energy', 'term': 'renewable energy', 'wiki_url': 'http://en.wikipedia.org/wiki/Renewable_energy', 'match': 'partial'}
{'term': 'a collection is a group of resources that have been selected for some purpose similar terms                    are set mathematics aggregation data modeling dataset science and                    business and corpus linguistics and literary analysis', 'match': 'none'}
{'term': 'an index is                    a description                        resource that contains information about the locations and                    frequencies of terms in a document collection to enable it to be searched                efficiently', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Assault', 'term': 'assault', 'wiki_url': 'http://en.wikipedia.org/wiki/Assault', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Homicide', 'term': 'homicide', 'wiki_url': 'http://en.wikipedia.org/wiki/Homicide', 'match': 'partial'}
{'term': 'selforganizing systems can                    change their internal structure or their function in response to feedback or                    changed circumstances', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Arrangement', 'term': 'arrangement', 'wiki_url': 'http://en.wikipedia.org/wiki/Arrangement', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Orchestration', 'term': 'orchestration', 'wiki_url': 'http://en.wikipedia.org/wiki/Orchestration', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Arrangement', 'term': 'arrangement', 'wiki_url': 'http://en.wikipedia.org/wiki/Arrangement', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Orchestration', 'term': 'orchestration', 'wiki_url': 'http://en.wikipedia.org/wiki/Orchestration', 'match': 'partial'}
{'term': 'it is highly desirable when the design and implementation of anorganizing system separates the storage of the resources from thelogic of their arrangement and the methods for interacting withthem this threetier architect is familiar to designers ofcomputerized organizing systems but it is also useful to think aboutorganizing systems in this way even when it involves physicalresources', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Sexism', 'term': 'sexism', 'wiki_url': 'http://en.wikipedia.org/wiki/Sexism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/MediaWiki', 'term': 'mediawiki', 'wiki_url': 'http://en.wikipedia.org/wiki/MediaWiki', 'match': 'partial'}
{'term': 'the organizing system                        for a small collection can sometimes use only the minimal or default                        organizing principle of collocation  putting                        all the resources in the same container on the same                            shelf  or in the same email inbox', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Excommunication', 'term': 'excommunication', 'wiki_url': 'http://en.wikipedia.org/wiki/Excommunication', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/CERN', 'term': 'cern', 'wiki_url': 'http://en.wikipedia.org/wiki/CERN', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Daily_Mirror', 'term': 'daily mirror', 'wiki_url': 'http://en.wikipedia.org/wiki/Daily_Mirror', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/William_Ewart_Gladstone', 'term': 'william ewart gladstone', 'wiki_url': 'http://en.wikipedia.org/wiki/William_Ewart_Gladstone', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Central_Intelligence_Agency', 'term': 'central intelligence agency', 'wiki_url': 'http://en.wikipedia.org/wiki/Central_Intelligence_Agency', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Free_agent', 'term': 'free agent', 'wiki_url': 'http://en.wikipedia.org/wiki/Free_agent', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Radio-frequency_identification', 'term': 'radio-frequency identification', 'wiki_url': 'http://en.wikipedia.org/wiki/Radio-frequency_identification', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Standardization', 'term': 'standardization', 'wiki_url': 'http://en.wikipedia.org/wiki/Standardization', 'match': 'partial'}
{'term': 'an interaction is an action  function  service  or capability that makes use of the resources in a collection                    or the collection as a whole the interaction of access is fundamental in any collection of                    resources but many organizing systems provide additional functions to make access more efficient                    and to support additional interactions with the accessed                    resources for example libraries and similar organizing systems implement                    catalogs to enable interactions for finding a known resource identifying any resource in the                    collection and discriminating or selecting among similar                    resources', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Daily_Mirror', 'term': 'daily mirror', 'wiki_url': 'http://en.wikipedia.org/wiki/Daily_Mirror', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/William_Ewart_Gladstone', 'term': 'william ewart gladstone', 'wiki_url': 'http://en.wikipedia.org/wiki/William_Ewart_Gladstone', 'match': 'partial'}
{'term': 'the original order of the                    resources in an archive embodies the implicit or explicit organizing system of                    the person or entity that created the documents and it is treated as an                    essential part of the meaning of the collection as a result the unit of                    organization for archival collections is the fonds  the                    original arrangement or grouping preserving any hierarchy of boxes  folders  envelopes  and individual documents  and thus they are not                    reorganized according to other perhaps more systematic                    classifications', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Curator', 'term': 'curator', 'wiki_url': 'http://en.wikipedia.org/wiki/Curator', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Collection_catalog', 'term': 'collection catalog', 'wiki_url': 'http://en.wikipedia.org/wiki/Collection_catalog', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Fortunately,_Unfortunately', 'term': 'fortunately, unfortunately', 'wiki_url': 'http://en.wikipedia.org/wiki/Fortunately,_Unfortunately', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Taxonomy', 'term': 'taxonomy', 'wiki_url': 'http://en.wikipedia.org/wiki/Taxonomy', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/K\xc3\xb6ppen_climate_classification', 'term': 'k\xc3\xb6ppen climate classification', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Paleo-Indians', 'term': 'paleo-indians', 'wiki_url': 'http://en.wikipedia.org/wiki/Paleo-Indians', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Cohabitation', 'term': 'cohabitation', 'wiki_url': 'http://en.wikipedia.org/wiki/Cohabitation', 'match': 'partial'}
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{'url': 'http://dbpedia.org/resource/Homology_(biology)', 'term': 'homology (biology)', 'wiki_url': 'http://en.wikipedia.org/wiki/Homology_(biology)', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Convergent_evolution', 'term': 'convergent evolution', 'wiki_url': 'http://en.wikipedia.org/wiki/Convergent_evolution', 'match': 'partial'}
{'url': "http://dbpedia.org/resource/Occam's_razor", 'term': "occam's razor", 'wiki_url': 'http://en.wikipedia.org/wiki/Occam%27s_razor', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Dependent_and_independent_variables', 'term': 'dependent and independent variables', 'wiki_url': 'http://en.wikipedia.org/wiki/Dependent_and_independent_variables', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Social_psychology', 'term': 'social psychology', 'wiki_url': 'http://en.wikipedia.org/wiki/Social_psychology', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Individualism', 'term': 'individualism', 'wiki_url': 'http://en.wikipedia.org/wiki/Individualism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Copyright', 'term': 'copyright', 'wiki_url': 'http://en.wikipedia.org/wiki/Copyright', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/State_school', 'term': 'state school', 'wiki_url': 'http://en.wikipedia.org/wiki/State_school', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Religion', 'term': 'religion', 'wiki_url': 'http://en.wikipedia.org/wiki/Religion', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Early_Christianity', 'term': 'early christianity', 'wiki_url': 'http://en.wikipedia.org/wiki/Early_Christianity', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Ancient_history', 'term': 'ancient history', 'wiki_url': 'http://en.wikipedia.org/wiki/Ancient_history', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Greatest_hits_album', 'term': 'greatest hits album', 'wiki_url': 'http://en.wikipedia.org/wiki/Greatest_hits_album', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Toll_road', 'term': 'toll road', 'wiki_url': 'http://en.wikipedia.org/wiki/Toll_road', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Hampshire', 'term': 'hampshire', 'wiki_url': 'http://en.wikipedia.org/wiki/Hampshire', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Homosexuality', 'term': 'homosexuality', 'wiki_url': 'http://en.wikipedia.org/wiki/Homosexuality', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Exchangeable_image_file_format', 'term': 'exchangeable image file format', 'wiki_url': 'http://en.wikipedia.org/wiki/Exchangeable_image_file_format', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Template:R_from_EXIF', 'term': 'template:r from exif', 'wiki_url': None, 'match': 'partial'}
{'url': "http://dbpedia.org/resource/Occam's_razor", 'term': "occam's razor", 'wiki_url': 'http://en.wikipedia.org/wiki/Occam%27s_razor', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Adaptive_reuse', 'term': 'adaptive reuse', 'wiki_url': 'http://en.wikipedia.org/wiki/Adaptive_reuse', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contract', 'term': 'contract', 'wiki_url': 'http://en.wikipedia.org/wiki/Contract', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Employment', 'term': 'employment', 'wiki_url': 'http://en.wikipedia.org/wiki/Employment', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Secretary', 'term': 'secretary', 'wiki_url': 'http://en.wikipedia.org/wiki/Secretary', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/1994_Winter_Olympics', 'term': '1994 winter olympics', 'wiki_url': 'http://en.wikipedia.org/wiki/1994_Winter_Olympics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/National_Football_League', 'term': 'national football league', 'wiki_url': 'http://en.wikipedia.org/wiki/National_Football_League', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Boxing', 'term': 'boxing', 'wiki_url': 'http://en.wikipedia.org/wiki/Boxing', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Segunda_Divisi\xc3\xb3n', 'term': 'segunda divisi\xc3\xb3n', 'wiki_url': None, 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Stellar_classification', 'term': 'stellar classification', 'wiki_url': 'http://en.wikipedia.org/wiki/Stellar_classification', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Judge', 'term': 'judge', 'wiki_url': 'http://en.wikipedia.org/wiki/Judge', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Metafiction', 'term': 'metafiction', 'wiki_url': 'http://en.wikipedia.org/wiki/Metafiction', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Historical_criticism', 'term': 'historical criticism', 'wiki_url': 'http://en.wikipedia.org/wiki/Historical_criticism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Standardization', 'term': 'standardization', 'wiki_url': 'http://en.wikipedia.org/wiki/Standardization', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/XML', 'term': 'xml', 'wiki_url': 'http://en.wikipedia.org/wiki/XML', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/HTML', 'term': 'html', 'wiki_url': 'http://en.wikipedia.org/wiki/HTML', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/CBS', 'term': 'cbs', 'wiki_url': 'http://en.wikipedia.org/wiki/CBS', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Microsoft_Windows', 'term': 'microsoft windows', 'wiki_url': 'http://en.wikipedia.org/wiki/Microsoft_Windows', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Species', 'term': 'species', 'wiki_url': 'http://en.wikipedia.org/wiki/Species', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Zoo', 'term': 'zoo', 'wiki_url': 'http://en.wikipedia.org/wiki/Zoo', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/CBS', 'term': 'cbs', 'wiki_url': 'http://en.wikipedia.org/wiki/CBS', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Microsoft_Windows', 'term': 'microsoft windows', 'wiki_url': 'http://en.wikipedia.org/wiki/Microsoft_Windows', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Windows_Desktop_Gadgets', 'term': 'windows desktop gadgets', 'wiki_url': 'http://en.wikipedia.org/wiki/Windows_Desktop_Gadgets', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Microsoft_Gadgets', 'term': 'microsoft gadgets', 'wiki_url': 'http://en.wikipedia.org/wiki/Microsoft_Gadgets', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Multiple_sclerosis', 'term': 'multiple sclerosis', 'wiki_url': 'http://en.wikipedia.org/wiki/Multiple_sclerosis', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Multilingualism', 'term': 'multilingualism', 'wiki_url': 'http://en.wikipedia.org/wiki/Multilingualism', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Metamodeling', 'term': 'metamodeling', 'wiki_url': 'http://en.wikipedia.org/wiki/Metamodeling', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Paragraph', 'term': 'paragraph', 'wiki_url': 'http://en.wikipedia.org/wiki/Paragraph', 'match': 'good-partial'}
{'term': 'an ', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/S._Harinarayana', 'term': 's. harinarayana', 'wiki_url': 'http://en.wikipedia.org/wiki/S._Harinarayana', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Count', 'term': 'count', 'wiki_url': 'http://en.wikipedia.org/wiki/Count', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Petroleum', 'term': 'petroleum', 'wiki_url': 'http://en.wikipedia.org/wiki/Petroleum', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Broadcast_syndication', 'term': 'broadcast syndication', 'wiki_url': 'http://en.wikipedia.org/wiki/Broadcast_syndication', 'match': 'partial'}
{'term': 'for', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/Local_Government_Act_1972', 'term': 'local government act 1972', 'wiki_url': 'http://en.wikipedia.org/wiki/Local_Government_Act_1972', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Plate_tectonics', 'term': 'plate tectonics', 'wiki_url': 'http://en.wikipedia.org/wiki/Plate_tectonics', 'match': 'partial'}
{'term': 'embodies', 'match': 'none'}
{'url': 'http://dbpedia.org/resource/International_Union_for_Conservation_of_Nature', 'term': 'international union for conservation of nature', 'wiki_url': 'http://en.wikipedia.org/wiki/International_Union_for_Conservation_of_Nature', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Renewable_energy', 'term': 'renewable energy', 'wiki_url': 'http://en.wikipedia.org/wiki/Renewable_energy', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Uniform_polyhedron', 'term': 'uniform polyhedron', 'wiki_url': 'http://en.wikipedia.org/wiki/Uniform_polyhedron', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Non-uniform_rational_B-spline', 'term': 'non-uniform rational b-spline', 'wiki_url': 'http://en.wikipedia.org/wiki/Non-uniform_rational_B-spline', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Subscription_business_model', 'term': 'subscription business model', 'wiki_url': 'http://en.wikipedia.org/wiki/Subscription_business_model', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Electronic_publishing', 'term': 'electronic publishing', 'wiki_url': 'http://en.wikipedia.org/wiki/Electronic_publishing', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/WiMAX', 'term': 'wimax', 'wiki_url': 'http://en.wikipedia.org/wiki/WiMAX', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Interoperability', 'term': 'interoperability', 'wiki_url': 'http://en.wikipedia.org/wiki/Interoperability', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Early_Christianity', 'term': 'early christianity', 'wiki_url': 'http://en.wikipedia.org/wiki/Early_Christianity', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Ancient_history', 'term': 'ancient history', 'wiki_url': 'http://en.wikipedia.org/wiki/Ancient_history', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Manufacturing', 'term': 'manufacturing', 'wiki_url': 'http://en.wikipedia.org/wiki/Manufacturing', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Cemetery', 'term': 'cemetery', 'wiki_url': 'http://en.wikipedia.org/wiki/Cemetery', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Charitable_organization', 'term': 'charitable organization', 'wiki_url': 'http://en.wikipedia.org/wiki/Charitable_organization', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/The_New_York_Times_Best_Seller_list', 'term': 'the new york times best seller list', 'wiki_url': 'http://en.wikipedia.org/wiki/The_New_York_Times_Best_Seller_list', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Substance_abuse', 'term': 'substance abuse', 'wiki_url': 'http://en.wikipedia.org/wiki/Substance_abuse', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Wheelchair', 'term': 'wheelchair', 'wiki_url': 'http://en.wikipedia.org/wiki/Wheelchair', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Right-wing_politics', 'term': 'right-wing politics', 'wiki_url': 'http://en.wikipedia.org/wiki/Right-wing_politics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Transport', 'term': 'transport', 'wiki_url': 'http://en.wikipedia.org/wiki/Transport', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Sherd', 'term': 'sherd', 'wiki_url': 'http://en.wikipedia.org/wiki/Sherd', 'match': 'good-partial'}
{'url': 'http://dbpedia.org/resource/Public_domain', 'term': 'public domain', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_domain', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Contributing_property', 'term': 'contributing property', 'wiki_url': 'http://en.wikipedia.org/wiki/Contributing_property', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/BBC_News', 'term': 'bbc news', 'wiki_url': 'http://en.wikipedia.org/wiki/BBC_News', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Trojan_War', 'term': 'trojan war', 'wiki_url': 'http://en.wikipedia.org/wiki/Trojan_War', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Sonar', 'term': 'sonar', 'wiki_url': 'http://en.wikipedia.org/wiki/Sonar', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Alluvium', 'term': 'alluvium', 'wiki_url': 'http://en.wikipedia.org/wiki/Alluvium', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Climate_change', 'term': 'climate change', 'wiki_url': 'http://en.wikipedia.org/wiki/Climate_change', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Global_warming', 'term': 'global warming', 'wiki_url': 'http://en.wikipedia.org/wiki/Global_warming', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/The_Church_of_Jesus_Christ_of_Latter-day_Saints', 'term': 'the church of jesus christ of latter-day saints', 'wiki_url': 'http://en.wikipedia.org/wiki/The_Church_of_Jesus_Christ_of_Latter-day_Saints', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Himalayas', 'term': 'himalayas', 'wiki_url': 'http://en.wikipedia.org/wiki/Himalayas', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Architect', 'term': 'architect', 'wiki_url': 'http://en.wikipedia.org/wiki/Architect', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Medicine', 'term': 'medicine', 'wiki_url': 'http://en.wikipedia.org/wiki/Medicine', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Nuclear_weapon', 'term': 'nuclear weapon', 'wiki_url': 'http://en.wikipedia.org/wiki/Nuclear_weapon', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Torture', 'term': 'torture', 'wiki_url': 'http://en.wikipedia.org/wiki/Torture', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Statistics', 'term': 'statistics', 'wiki_url': 'http://en.wikipedia.org/wiki/Statistics', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Molecule', 'term': 'molecule', 'wiki_url': 'http://en.wikipedia.org/wiki/Molecule', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Intellectual', 'term': 'intellectual', 'wiki_url': 'http://en.wikipedia.org/wiki/Intellectual', 'match': 'exact'}
{'url': 'http://dbpedia.org/resource/Scientific_journal', 'term': 'scientific journal', 'wiki_url': 'http://en.wikipedia.org/wiki/Scientific_journal', 'match': 'partial'}
{'url': 'http://dbpedia.org/resource/Public_speaking', 'term': 'public speaking', 'wiki_url': 'http://en.wikipedia.org/wiki/Public_speaking', 'match': 'partial'}
In [20]:
print len(list_for_wiki_df)
new_cols_df = pd.DataFrame(list_for_wiki_df)
1154
In [21]:
## extract the exact matches
exact_match = new_cols_df[new_cols_df['match'] == 'exact']
exact_match[:10]
Out[21]:
count match matched_term term url
8 1 exact metadata metadata http://en.wikipedia.org/wiki/Metadata
60 1 exact cataloging cataloging http://en.wikipedia.org/wiki/Cataloging
108 1 exact adam smith smith, adam http://en.wikipedia.org/wiki/Adam_Smith
109 1 exact charles darwin darwin, charles http://en.wikipedia.org/wiki/Charles_Darwin
116 1 exact cern cern http://en.wikipedia.org/wiki/CERN
151 1 exact collocation collocation http://en.wikipedia.org/wiki/Collocation
178 1 exact ifla ifla http://en.wikipedia.org/wiki/IFLA
309 1 exact cataloging cataloging http://en.wikipedia.org/wiki/Cataloging
312 1 exact ronald coase coase, ronald http://en.wikipedia.org/wiki/Ronald_Coase
313 1 exact adam smith smith, adam http://en.wikipedia.org/wiki/Adam_Smith
In [22]:
## extract the good matches
good_match = new_cols_df[new_cols_df['match'] == 'good-partial']
In [23]:
## extract the partial matches
partial_match = new_cols_df[new_cols_df['match'] == 'partial']
In [24]:
## Create a DataFrame with only good-partial and exact match terms
matched_terms = good_match.append(exact_match)
In [26]:
matched_terms
Out[26]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 158 entries, 33 to 1151
Data columns:
count           158  non-null values
match           158  non-null values
matched_term    158  non-null values
term            158  non-null values
url             158  non-null values
dtypes: int64(1), object(4)
In [25]:
## first 10 matched_terms
matched_terms[:10]
Out[25]:
count match matched_term term url
33 1 good-partial geoffrey nunberg nunberg, geoff http://en.wikipedia.org/wiki/Geoffrey_Nunberg
73 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI
76 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI
99 1 good-partial data set dataset http://en.wikipedia.org/wiki/Data_set
243 1 good-partial sergey brin brin, sergei http://en.wikipedia.org/wiki/Sergey_Brin
252 1 good-partial paul samuelson samuelson, pamela http://en.wikipedia.org/wiki/Paul_Samuelson
259 1 good-partial hathitrust hathi trust http://en.wikipedia.org/wiki/HathiTrust
266 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku
306 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku
320 1 good-partial moore's law moore's law http://en.wikipedia.org/wiki/Moore%27s_law

After we get the Wikipedia URL, we use Wiki2Plain to extract the page summary and image for the matched_terms

We chose "exact" and "good-partial" matches for Wikipedia linking. Many of the terms returned correct results (see results below), while some returned incorrect pages, e.g. Radio Televisione Italiana for URI. This shows the challenge of finding good results when looking up Wikipedia URLs. The class Wiki2Plain, allows us to scrape the summary and image from a Wikipedia page. The class is available in the Appendix and on Github.

In [38]:
## function using Wiki2Plain results to create two new DataFrame columns using apply
def get_wiki_textimage(url):
    print url
    try:
        wiki = Wiki2Plain(url)
    except:
        return "none","none"
    return wiki.text, wiki.image()
In [39]:
## apply and use tuple result to create two DataFrames
## from http://manishamde.github.io/blog/2013/03/07/pandas-and-python-top-10/#create

matched_terms['wiki_text'],matched_terms['wiki_image'] = zip(*matched_terms['url'].apply(get_wiki_textimage))
http://en.wikipedia.org/wiki/Geoffrey_Nunberg
http://en.wikipedia.org/wiki/RAI
http://en.wikipedia.org/wiki/RAI
http://en.wikipedia.org/wiki/Data_set
http://en.wikipedia.org/wiki/Sergey_Brin
http://en.wikipedia.org/wiki/Paul_Samuelson
http://en.wikipedia.org/wiki/HathiTrust
http://en.wikipedia.org/wiki/Tulku
http://en.wikipedia.org/wiki/Tulku
http://en.wikipedia.org/wiki/Moore%27s_law
http://en.wikipedia.org/wiki/Geoffrey_Nunberg
http://en.wikipedia.org/wiki/Tim_O'Reilly
http://en.wikipedia.org/wiki/Yahoo!
http://en.wikipedia.org/wiki/Yahoo!
http://en.wikipedia.org/wiki/DVD
http://en.wikipedia.org/wiki/Presenter
http://en.wikipedia.org/wiki/Clothing
http://en.wikipedia.org/wiki/Interdependence
http://en.wikipedia.org/wiki/Museum
http://en.wikipedia.org/wiki/Pula
http://en.wikipedia.org/wiki/Concept_car
http://en.wikipedia.org/wiki/Separatism
http://en.wikipedia.org/wiki/Home_page
http://en.wikipedia.org/wiki/Sidebar
http://en.wikipedia.org/wiki/Implementation
http://en.wikipedia.org/wiki/MP3
http://en.wikipedia.org/wiki/Algorithm
http://en.wikipedia.org/wiki/Exhibition
http://en.wikipedia.org/wiki/Writer
http://en.wikipedia.org/wiki/History
http://en.wikipedia.org/wiki/School
http://en.wikipedia.org/wiki/Merchant
http://en.wikipedia.org/wiki/Camera
http://en.wikipedia.org/wiki/Stratum
http://en.wikipedia.org/wiki/Grape
http://en.wikipedia.org/wiki/Sensor
http://en.wikipedia.org/wiki/Cookbook
http://en.wikipedia.org/wiki/Neighbourhood
http://en.wikipedia.org/wiki/Consistency
http://en.wikipedia.org/wiki/Operating_system
http://en.wikipedia.org/wiki/Enabling
http://en.wikipedia.org/wiki/LIFO
http://en.wikipedia.org/wiki/Gas
http://en.wikipedia.org/wiki/PAL
http://en.wikipedia.org/wiki/Heuristic
http://en.wikipedia.org/wiki/Solution
http://en.wikipedia.org/wiki/Textbook
http://en.wikipedia.org/wiki/Encyclopedia
http://en.wikipedia.org/wiki/Moore's_law
http://en.wikipedia.org/wiki/NPR
http://en.wikipedia.org/wiki/Psychologist
http://en.wikipedia.org/wiki/Analogy
http://en.wikipedia.org/wiki/Telecommunication
http://en.wikipedia.org/wiki/V8_engine
http://en.wikipedia.org/wiki/Internet
http://en.wikipedia.org/wiki/Speech
http://en.wikipedia.org/wiki/Soap
http://en.wikipedia.org/wiki/Employment
http://en.wikipedia.org/wiki/Hangar
http://en.wikipedia.org/wiki/Image
http://en.wikipedia.org/wiki/Utilitarianism
http://en.wikipedia.org/wiki/Temple
http://en.wikipedia.org/wiki/Europe
http://en.wikipedia.org/wiki/Bicycle
http://en.wikipedia.org/wiki/Cycling
http://en.wikipedia.org/wiki/Yahoo!
http://en.wikipedia.org/wiki/Copyright
http://en.wikipedia.org/wiki/Species
http://en.wikipedia.org/wiki/Zoo
http://en.wikipedia.org/wiki/Metamodeling
http://en.wikipedia.org/wiki/Paragraph
http://en.wikipedia.org/wiki/S._Harinarayana
http://en.wikipedia.org/wiki/Count
http://en.wikipedia.org/wiki/Sherd
http://en.wikipedia.org/wiki/Metadata
http://en.wikipedia.org/wiki/Cataloging
http://en.wikipedia.org/wiki/Adam_Smith
http://en.wikipedia.org/wiki/Charles_Darwin
http://en.wikipedia.org/wiki/CERN
http://en.wikipedia.org/wiki/Collocation
http://en.wikipedia.org/wiki/IFLA
http://en.wikipedia.org/wiki/Cataloging
http://en.wikipedia.org/wiki/Ronald_Coase
http://en.wikipedia.org/wiki/Adam_Smith
http://en.wikipedia.org/wiki/EXIF
http://en.wikipedia.org/wiki/EBay
http://en.wikipedia.org/wiki/Twitter
http://en.wikipedia.org/wiki/Facebook
http://en.wikipedia.org/wiki/Folksonomy
http://en.wikipedia.org/wiki/Flickr
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/SeaWorld
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Flickr
http://en.wikipedia.org/wiki/Westlaw
http://en.wikipedia.org/wiki/LexisNexis
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/EBay
http://en.wikipedia.org/wiki/Wikipedia
http://en.wikipedia.org/wiki/Facebook
http://en.wikipedia.org/wiki/Twitter
http://en.wikipedia.org/wiki/YouTube
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Microsoft
http://en.wikipedia.org/wiki/Google
http://en.wikipedia.org/wiki/Microsoft
http://en.wikipedia.org/wiki/Herman_Melville
http://en.wikipedia.org/wiki/Adam_Smith
http://en.wikipedia.org/wiki/Charles_Darwin
http://en.wikipedia.org/wiki/Computer_science
http://en.wikipedia.org/wiki/Cooking
http://en.wikipedia.org/wiki/Metadata
http://en.wikipedia.org/wiki/Granularity
http://en.wikipedia.org/wiki/Economics
http://en.wikipedia.org/wiki/Law
http://en.wikipedia.org/wiki/Castle
http://en.wikipedia.org/wiki/Wine
http://en.wikipedia.org/wiki/Synonyms
http://en.wikipedia.org/wiki/Windshield
http://en.wikipedia.org/wiki/Coffee
http://en.wikipedia.org/wiki/Aisle
http://en.wikipedia.org/wiki/Historian
http://en.wikipedia.org/wiki/Fiction
http://en.wikipedia.org/wiki/Geneva
http://en.wikipedia.org/wiki/Tool
http://en.wikipedia.org/wiki/EBay
http://en.wikipedia.org/wiki/Iron
http://en.wikipedia.org/wiki/Bridge
http://en.wikipedia.org/wiki/Fashion
http://en.wikipedia.org/wiki/IBM
http://en.wikipedia.org/wiki/Chess
http://en.wikipedia.org/wiki/Phonograph
http://en.wikipedia.org/wiki/Anatomy
http://en.wikipedia.org/wiki/Reimbursement
http://en.wikipedia.org/wiki/Grass
http://en.wikipedia.org/wiki/Nobel_Prize
http://en.wikipedia.org/wiki/Keywords
http://en.wikipedia.org/wiki/Architecture
http://en.wikipedia.org/wiki/Bookmarking
http://en.wikipedia.org/wiki/Kitchen
http://en.wikipedia.org/wiki/Papyrus
http://en.wikipedia.org/wiki/Logic
http://en.wikipedia.org/wiki/Negotiation
http://en.wikipedia.org/wiki/Website
http://en.wikipedia.org/wiki/Publisher
http://en.wikipedia.org/wiki/Physician
http://en.wikipedia.org/wiki/Complexity
http://en.wikipedia.org/wiki/Business
http://en.wikipedia.org/wiki/Human
http://en.wikipedia.org/wiki/Instantiation
http://en.wikipedia.org/wiki/Judge
http://en.wikipedia.org/wiki/Standardization
http://en.wikipedia.org/wiki/Manufacturing
http://en.wikipedia.org/wiki/Cemetery
http://en.wikipedia.org/wiki/Intellectual
In [94]:
## first ten terms
matched_terms[:10]
Out[94]:
count match matched_term term url wiki_text wiki_image flickr_urls
33 1 good-partial geoffrey nunberg nunberg, geoff http://en.wikipedia.org/wiki/Geoffrey_Nunberg Geoffrey Nunberg (born June, 1945) is an Ameri... None [http://farm9.staticflickr.com/8140/8700510731...
73 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI RAI — Radiotelevisione Italiana S.p.A. (... None [http://farm9.staticflickr.com/8269/8699910887...
76 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI RAI — Radiotelevisione Italiana S.p.A. (... None [http://farm9.staticflickr.com/8269/8699910887...
99 1 good-partial data set dataset http://en.wikipedia.org/wiki/Data_set A dataset (or data set) is a collection of dat... None [http://farm9.staticflickr.com/8527/8590445473...
243 1 good-partial sergey brin brin, sergei http://en.wikipedia.org/wiki/Sergey_Brin Sergey Mikhaylovich Brin (Сергей Михайлович Бр... http://simple.wikipedia.org/w/index.php?title=... [http://farm9.staticflickr.com/8407/8699842532...
252 1 good-partial paul samuelson samuelson, pamela http://en.wikipedia.org/wiki/Paul_Samuelson Paul Anthony Samuelson (May 15, 1915 – Decembe... http://simple.wikipedia.org/w/index.php?title=... [http://farm9.staticflickr.com/8280/8700678957...
259 1 good-partial hathitrust hathi trust http://en.wikipedia.org/wiki/HathiTrust HathiTrust is a large-scale collaborative repo... None [http://farm8.staticflickr.com/7088/7178341310...
266 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku In Tibetan Buddhism, "tulku" (, also tülku, tr... None [http://farm9.staticflickr.com/8113/8698495870...
306 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku In Tibetan Buddhism, "tulku" (, also tülku, tr... None [http://farm9.staticflickr.com/8113/8698495870...
320 1 good-partial moore's law moore's law http://en.wikipedia.org/wiki/Moore%27s_law none none [http://farm9.staticflickr.com/8230/8597007467...

Our result for Adam Smith (DataFram index 158)

In [70]:
# http://ipython.org/ipython-doc/dev/api/generated/IPython.core.display.html#IPython.core.display.Image
# width is IPython 14+, this is IPython version 0.13.1
from IPython.core.display import Image
print matched_terms.ix[243]['wiki_text']
Image(url=matched_terms.ix[243]['wiki_image'])
Sergey Mikhaylovich Brin (Сергей Михайлович Брин) (born August 21, 1973) is an American computer scientist and Internet entrepreneur who, with Larry Page, co-founded Google, one of the most profitable Internet companies. , his personal wealth is estimated to be $20.3 billion. Together, Brin and Page own about 16 percent of the company.

Brin immigrated to the United States with his family from the Soviet Union at the age of six. He earned his undergraduate degree at the University of Maryland, following in his father's and grandfather's footsteps by studying mathematics, as well as computer science. After graduation, he moved to Stanford University to acquire a Ph.D. in computer science. There he met Larry Page, with whom he later became friends. They crammed their dormitory room with inexpensive computers and applied Brin's data mining system to build a superior search engine. The program became popular at Stanford and they suspended their PhD studies to start up Google in a rented garage.

The Economist newspaper referred to Brin as an "Enlightenment Man", and someone who believes that "knowledge is always good, and certainly always better than ignorance", a philosophy that is summed up by Google’s motto "Organize the world’s information and make it universally accessible and useful" and "Don't be evil".


Out[70]:

Other APIs - Flickr and News (Guardian)

Our project also explored the use of Flickr and News APIs that run queries based on the terms matched from Wikipedia. These are potentially useful in various ways.

In [105]:
## load imports and API Keys
from flickr_api.auth import AuthHandler
from flickr_api import FlickrError
import flickr_api
from tidings import Guardian, NewYorkTimes

def load_api_keys():
    if os.path.exists('settings.py'):
        from settings import FLICKR_KEY, FLICKR_SECRET, guardian_key, nyt_key
        secrets = {'api_key': FLICKR_KEY, 'api_secret': FLICKR_SECRET}
        news_keys = {'guardian_key': guardian_key, 'nyt_key': nyt_key }
        return secrets, news_keys
    else:
        print("settings.py not found, add to directory or run without flickr and news")
        sys.exit()

secrets, news_keys = load_api_keys()

Flickr

In [72]:
def get_flickr_url(term):
    flickr_api.set_keys(**secrets)
    photos = flickr_api.Photo.search(tags=term, sort='date-posted-desc')
 
    if len(photos) == 0 or type(photos) == dict:
        return []
    
    flickr_urls = []
    for photo in photos[:3]:
        try:
            flickr_urls.append("http://farm{farm}.staticflickr.com/{server}/{id}_{secret}_m.jpg".format(**photo.getInfo()))
        except FlickrError:
            pass

    return flickr_urls

matched_terms['flickr_urls'] = matched_terms['term'].apply(get_flickr_url)
In [99]:
## which flickr images did we get for the term 'museums'?
print matched_terms.ix[565]['term']
flickr_url = matched_terms.ix[565]['flickr_urls'][1]
Image(url=flickr_url)
museums
Out[99]:

Guardian UK

In [113]:
## blocked from API?
def get_news_url(term):
    g = Guardian(news_keys['guardian_key'])
    print term
    g_links = g.query(re.sub("\W","",term), from_date='2013-01-01', to_date='2013-4-30')
    return g_links[:3]

matched_terms['news_urls'], = matched_terms['term'].apply(get_news_url)
---------------------------------------------------------------------------
HTTPError                                 Traceback (most recent call last)
<ipython-input-113-e79027e0d9e3> in <module>()
      5     return g_links[:3]
      6 
----> 7 matched_terms['news_urls'], = matched_terms['term'].apply(get_news_url)

/Library/Python/2.7/site-packages/pandas-0.10.1-py2.7-macosx-10.8-intel.egg/pandas/core/series.pyc in apply(self, func, convert_dtype, args, **kwds)
   2294             values = lib.map_infer(values, lib.Timestamp)
   2295 
-> 2296         mapped = lib.map_infer(values, f, convert=convert_dtype)
   2297         if isinstance(mapped[0], Series):
   2298             from pandas.core.frame import DataFrame

/Library/Python/2.7/site-packages/pandas-0.10.1-py2.7-macosx-10.8-intel.egg/pandas/lib.so in pandas.lib.map_infer (pandas/lib.c:39944)()

<ipython-input-113-e79027e0d9e3> in get_news_url(term)
      2     g = Guardian(news_keys['guardian_key'])
      3     print term
----> 4     g_links = g.query(re.sub("\W","",term), from_date='2013-01-01', to_date='2013-4-30')
      5     return g_links[:3]
      6 

/Users/ajrenold/Dropbox/iSchool/2013Spring/OpenData/doctorbook/doctorbook/notebooks/tidings.pyc in query(self, query, from_date, to_date)
     33         def query(self, query, from_date=date.today().strftime('%Y-01-01'), to_date=date.today().strftime('%Y-%m-%d')):
     34                 out_list = []
---> 35                 raw_response = self._request(query, from_date, to_date)
     36                 json_response = json.loads(raw_response)
     37                 out_list += self._process_result(json_response)#raw_response

/Users/ajrenold/Dropbox/iSchool/2013Spring/OpenData/doctorbook/doctorbook/notebooks/tidings.pyc in _request(self, query, from_date, to_date, page)
     22 		}
     23                 api_response = requests.get(endpoint, params=payload)
---> 24                 api_response.raise_for_status()
     25                 return api_response.text
     26 

/Library/Python/2.7/site-packages/requests/models.pyc in raise_for_status(self)
    636             http_error = HTTPError(http_error_msg)
    637             http_error.response = self
--> 638             raise http_error
    639 
    640     def close(self):

HTTPError: 403 Client Error: Forbidden
nunberg, geoff
In [115]:
matched_terms[:10]
Out[115]:
count match matched_term term url wiki_text wiki_image flickr_urls
33 1 good-partial geoffrey nunberg nunberg, geoff http://en.wikipedia.org/wiki/Geoffrey_Nunberg Geoffrey Nunberg (born June, 1945) is an Ameri... None [http://farm9.staticflickr.com/8140/8700510731...
73 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI RAI — Radiotelevisione Italiana S.p.A. (... None [http://farm9.staticflickr.com/8269/8699910887...
76 1 good-partial rai uri http://en.wikipedia.org/wiki/RAI RAI — Radiotelevisione Italiana S.p.A. (... None [http://farm9.staticflickr.com/8269/8699910887...
99 1 good-partial data set dataset http://en.wikipedia.org/wiki/Data_set A dataset (or data set) is a collection of dat... None [http://farm9.staticflickr.com/8527/8590445473...
243 1 good-partial sergey brin brin, sergei http://en.wikipedia.org/wiki/Sergey_Brin Sergey Mikhaylovich Brin (Сергей Михайлович Бр... http://simple.wikipedia.org/w/index.php?title=... [http://farm9.staticflickr.com/8407/8699842532...
252 1 good-partial paul samuelson samuelson, pamela http://en.wikipedia.org/wiki/Paul_Samuelson Paul Anthony Samuelson (May 15, 1915 – Decembe... http://simple.wikipedia.org/w/index.php?title=... [http://farm9.staticflickr.com/8280/8700678957...
259 1 good-partial hathitrust hathi trust http://en.wikipedia.org/wiki/HathiTrust HathiTrust is a large-scale collaborative repo... None [http://farm8.staticflickr.com/7088/7178341310...
266 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku In Tibetan Buddhism, "tulku" (, also tülku, tr... None [http://farm9.staticflickr.com/8113/8698495870...
306 1 good-partial tulku sku http://en.wikipedia.org/wiki/Tulku In Tibetan Buddhism, "tulku" (, also tülku, tr... None [http://farm9.staticflickr.com/8113/8698495870...
320 1 good-partial moore's law moore's law http://en.wikipedia.org/wiki/Moore%27s_law none none [http://farm9.staticflickr.com/8230/8597007467...

Future Project Direction

As a potentially useful tool for augmenting the reading experience with Open Data. Our group envisions two potential directions for our project or similar

  1. Pre-publishing Processing - where a non-fiction book in its raw form (such as DocBook XML) goes through a process where Open Data sources, such as a Wikipedia links, are inserted into the mark up. This step would take hours to run for an entire book. This would need improvement in the match quality algorithm and possibly human quality assurance of the inserted links.
  2. Reading-time Ereader Extension - where our tool (shown in the prototype) could be built as an extension to an open source ereader, such as the product under development by FuturePress. The extension would annotate any document a user is reading at reading-time with annotations linking entities to their Wikipedia pages. For this use case our matching algorithm would need a lot of improvement!

Appendix

Note on Python String Encoding

From http://farmdev.com/talks/unicode/

When retrieving text from web resources and APIs and then storing the text, it is important to strictly convert strings to unicode. This will help to handle non-ascii characters before unicode only charaters start to create mystical bugs in the application. Areas where we ran into string encoding problems were attempting to store an DataFrame as a csv file and doing string comparisons (Can't compare a non-unicode string to a unicode string!).

Save/Open Data Frame

In [73]:
## write DataFrame
import os
path = os.getcwd() + '/wiki_urls_saved.csv'
encoding = 'UTF-8'
sep = ','
matched_terms.to_csv(path,sep,encoding)
In [ ]:
## read DataFrame
new_df = pd.read_csv(path)
new_df = new_df.drop(['Unnamed: 0'],axis=1)

WikiUrlFetch Class (two working versions WikiUrlFetch and WikiUrlFetchNonDBPedia)

In [ ]:
#!/usr/bin/env python

from urllib2 import urlopen
import urllib2
import re
import json
from nltk import metrics
from bs4 import BeautifulSoup, Tag

class WikiUrlFetch():

    def __init__(self):
        self.cleaned_term = None

    def fetch_wiki(self,term):
        self.cleaned_term = self.clean_term(term)
        self.results = self.get_wiki_url(self.cleaned_term)
        return self.results

    def clean_term(self,term):
        return re.sub(r"[^A-Za-z0-9 ]","",term.lower())
        
    def check_dbpedia(self, term):
        api = 'http://lookup.dbpedia.org/api/search.asmx/KeywordSearch?MaxHits=5&QueryString='
        #api = 'http://lookup.dbpedia.org/api/search.asmx/PrefixSearch?MaxHits=10&QueryString='
       
        #print term

        try:
            response = urlopen(api+term)
        except:
            return ""
    
        soup = BeautifulSoup(response.read())
    
        results = []
        for result in soup.findAll('result'):
            for child in result.children:
                if isinstance(child,Tag):
                    if child.name == 'label':
                        current_label = child.string.lower()
                    if child.name == 'uri':
                        results.append({ 'term': current_label.encode('utf-8'), 'url': child.string.encode('utf-8') })
        
        return self.rank_dbpedia_results(results,term)
    
    def normalize(self,string):
        strings = string.split(" ")
        strings.sort()
        return " ".join(strings)

    def rank_dbpedia_results(self,results,term):
        """
        logic:
            if edit distance 0, exact match
            if edit distance 1-4, good-partial match
            if edit distance > 4, partial match (results unsorted)
        """

        matches = []
        for result in results:
            matches.append([metrics.edit_distance(self.normalize(result['term']), self.normalize(term)), result])

        matches.sort()
        #print matches
        if len(matches) == 0:
            return [ { 'match': 'none', 'term': term.encode('utf-8') } ] 
        
        elif matches[0][0] == 0:
            new_results = [ matches[0][1] ]
            new_results[0]['match'] = 'exact'
            return new_results

        elif matches[0][0] <= 8:
            new_results = []
            for match in matches:
                if match[0] <= 3:
                    result = match[1]
                    result['match'] = 'good-partial'
                    new_results.append(result)

                """ # needs refinement to provide good matches
                elif match[0] <= 5:
                    words = self.normalize(result['term']).split(' ')
                    if self.normalize(term) in words:
                        result = match[1]
                        result['match'] = 'good-partial'
                        new_results.append(result)
                """
            return new_results

        else:
            new_results = []
            for result in results[0:2]:
                result['match'] = 'partial'
                new_results.append(result)
            return new_results
    
    def wiki_url(self,url):

        term = url[url.rfind('/'):]
        entity_page = 'http://dbpedia.org/data/{}.json'.format(term)
    
        wiki_type = 'http://xmlns.com/foaf/0.1/primaryTopic'
    
        try:
            response = urlopen(entity_page)
        except:
            return
    
        data = json.loads(response.read())
        for key,value in data.items():
            'http://xmlns.com/foaf/0.1/primaryTopic'
            if 'http://xmlns.com/foaf/0.1/primaryTopic' in value:
                #print key
                return key.encode('utf-8')

    def get_wiki_url(self, term):
    
        results = self.check_dbpedia(term)

        for result in results:
            if result['match'] != 'none' and result['match'] != 'partial':
                wiki = self.wiki_url(result['url'])
                result['wiki_url'] = wiki

        return results

class WikiUrlFetchNonDBPedia():

    def __init__(self):
        self.wiki_api =  'http://en.wikipedia.org/w/api.php?action=query&list=search&format=json&srsearch='
        self.cleaned_term = None

    def fetch_wiki(self,term):
        self.cleaned_term = self.clean_term(term)
        self.results = self.get_wiki_url(self.cleaned_term)
        return self.results

    def check_wikipedia_api(self,term):

        url = self.wiki_api+re.sub(' ','_',term)
        request = urllib2.Request(url)
        request.add_header('User-Agent', 'Mozilla/5.0')

        try:
            response = urlopen(request)
        except urllib2.HTTPError, e:
            print e.code
            return
        except urllib2.URLError, e:
            print e.reason
            return

        results = []
        data = json.loads(response.read())
        for key,value in data.items():
            if 'search' in value:
                if type(value['search']) == list:
                    results = self.parse_wikipedia_results(value['search'])

        if len(results) > 0:
            return self.rank_dbpedia_results(results,term)
        else:
            return [ { 'match': 'none', 'term': term.encode('utf-8') } ]

    def parse_wikipedia_results(self,results):
        base_wikipedia_url = 'http://en.wikipedia.org/wiki/'
        wiki_urls = []
        for result in results:
            if 'title' in result:
                wiki_urls.append( \
                { 'url': (base_wikipedia_url + re.sub(' ','_',result['title'])).encode('UTF-8') , \
                'term': result['title'].encode('UTF-8') } )

        return wiki_urls

    def clean_term(self,term):
        return re.sub(r"[^A-Za-z0-9 ]","",term.lower())

    def normalize(self,string):
        strings = string.lower().split(" ")
        strings.sort()
        return " ".join(strings)

    def rank_dbpedia_results(self,results,term):
        """
        logic:
            if edit distance 0, exact match
            if edit distance 1-4, good-partial match
            if edit distance > 4, partial match (results unsorted)
        """

        matches = []
        for result in results:
            matches.append([metrics.edit_distance(self.normalize(result['term']), self.normalize(term)), result])

        matches.sort()
        print term,matches
        print
        if len(matches) == 0:
            return [ { 'match': 'none', 'term': term.encode('utf-8') } ] 

        elif matches[0][0] == 0:
            new_results = [ matches[0][1] ]
            new_results[0]['match'] = 'exact'
            return new_results

        elif matches[0][0] <= 5:
            new_results = []
            for match in matches:
                if match[0] <= 3:
                    result = match[1]
                    result['match'] = 'good-partial'
                    new_results.append(result)

                # needs refinement to provide good matches
                elif match[0] <= 5:
                    words = self.normalize(result['term']).split(' ')
                    if self.normalize(term) in words:
                        result = match[1]
                        result['match'] = 'good-partial'
                        new_results.append(result)

            return new_results

        else:
            new_results = []
            for result in results[0:2]:
                result['match'] = 'partial'
                new_results.append(result)
            return new_results

    def get_wiki_url(self, term):

        results = self.check_wikipedia_api(term)

        for result in results:
            if result['match'] != 'none' and result['match'] != 'partial':
                result['wiki_url'] = result['url']
                

        #print results
        return results

Wiki2Plain Class

In [ ]:
# source: http://stackoverflow.com/questions/4460921/extract-the-first-paragraph-from-a-wikipedia-article-python/4461624#4461624
#!/usr/bin/env python

import re
import yaml
import urllib
import urllib2

class WikipediaError(Exception):
    pass

class Wikipedia:
    url_article = 'http://%s.wikipedia.org/w/index.php?action=raw&title=%s'
    url_image = 'http://%s.wikipedia.org/w/index.php?title=Special:FilePath&file=%s'
    url_search = 'http://%s.wikipedia.org/w/api.php?action=query&list=search&srsearch=%s&sroffset=%d&srlimit=%d&format=yaml'
    
    def __init__(self, lang):
        self.lang = lang
    
    def __fetch(self, url):
        request = urllib2.Request(url)
        request.add_header('User-Agent', 'Mozilla/5.0')
        
        try:
            result = urllib2.urlopen(request)
        except urllib2.HTTPError, e:
            raise WikipediaError(e.code)
        except urllib2.URLError, e:
            raise WikipediaError(e.reason)
        
        return result
    
    def article(self, url):
        article = url[url.rfind('/')+1:]
        url = self.url_article % (self.lang, urllib.quote_plus(article))
        content = self.__fetch(url).read()
        
        if content.upper().startswith('#REDIRECT'):
            match = re.match('(?i)#REDIRECT \[\[([^\[\]]+)\]\]', content)
            
            if not match == None:
                return self.article(match.group(1))
            
            raise WikipediaError('Can\'t found redirect article.')
        
        return content
    
    def image(self, image, thumb=None):
        url = self.url_image % (self.lang, image)
        result = self.__fetch(url)
        content = result.read()
        
        if thumb:
            url = result.geturl() + '/' + thumb + 'px-' + image
            url = url.replace('/commons/', '/commons/thumb/')
            url = url.replace('/' + self.lang + '/', '/' + self.lang + '/thumb/')
            
            return self.__fetch(url).read()
        
        return content
    
    def search(self, query, page=1, limit=10):
        offset = (page - 1) * limit
        url = self.url_search % (self.lang, urllib.quote_plus(query), offset, limit)
        content = self.__fetch(url).read()
        
        parsed = yaml.load(content)
        search = parsed['query']['search']
        
        results = []
        
        if search:
            for article in search:
                title = article['title'].strip()
                
                snippet = article['snippet']
                snippet = re.sub(r'(?m)<.*?>', '', snippet)
                snippet = re.sub(r'\s+', ' ', snippet)
                snippet = snippet.replace(' . ', '. ')
                snippet = snippet.replace(' , ', ', ')
                snippet = snippet.strip()
                
                wordcount = article['wordcount']
                
                results.append({
                    'title' : title,
                    'snippet' : snippet,
                    'wordcount' : wordcount
                })
        
        # yaml.dump(results, default_style='', default_flow_style=False,
        #     allow_unicode=True)
        return results

class Wiki2Plain:
#    url_article = 'http://%s.wikipedia.org/w/index.php?action=raw&title=%s'
    url_image = 'http://%s.wikipedia.org/w/index.php?title=Special:FilePath&file=%s'
#    url_search = 'http://%s.wikipedia.org/w/api.php?action=query&list=search&srsearch=%s&sroffset=%d&srlimit=%d&format=yaml'
    
    def __init__(self, url):
        self.wiki = Wikipedia('en')
        self.wiki_article = self.wiki.article(url)

        self.text = self.wiki_article
        self.text = self.unhtml(self.text)
        self.text = self.unwiki(self.text)
        self.text = self.punctuate(self.text)
        self.text = self.get_summary(self.text)
    
    def __str__(self):
        return self.text
    
    def unwiki(self, wiki):
        """
        Remove wiki markup from the text.
        """
        wiki = re.sub(r'(?i)\{\{IPA(\-[^\|\{\}]+)*?\|([^\|\{\}]+)(\|[^\{\}]+)*?\}\}', lambda m: m.group(2), wiki)
        wiki = re.sub(r'(?i)\{\{Lang(\-[^\|\{\}]+)*?\|([^\|\{\}]+)(\|[^\{\}]+)*?\}\}', lambda m: m.group(2), wiki)
        wiki = re.sub(r'\{\{[^\{\}]+\}\}', '', wiki)
        wiki = re.sub(r'(?m)\{\{[^\{\}]+\}\}', '', wiki)
        wiki = re.sub(r'(?m)\{\|[^\{\}]*?\|\}', '', wiki)
        wiki = re.sub(r'(?i)\[\[Category:[^\[\]]*?\]\]', '', wiki)
        wiki = re.sub(r'(?i)\[\[Image:[^\[\]]*?\]\]', '', wiki)
        wiki = re.sub(r'(?i)\[\[File:[^\[\]]*?\]\]', '', wiki)
        wiki = re.sub(r'\[\[[^\[\]]*?\|([^\[\]]*?)\]\]', lambda m: m.group(1), wiki)
        wiki = re.sub(r'\[\[([^\[\]]+?)\]\]', lambda m: m.group(1), wiki)
        wiki = re.sub(r'\[\[([^\[\]]+?)\]\]', '', wiki)
        wiki = re.sub(r'(?i)File:[^\[\]]*?', '', wiki)
        wiki = re.sub(r'\[[^\[\]]*? ([^\[\]]*?)\]', lambda m: m.group(1), wiki)
        wiki = re.sub(r"''+", '', wiki)
        wiki = re.sub(r'(?m)^\*$', '', wiki)
        
        return wiki
    
    def unhtml(self, html):
        """
        Remove HTML from the text.
        """
        html = re.sub(r'(?i)&nbsp;', ' ', html)
        html = re.sub(r'(?i)<br[ \\]*?>', '\n', html)
        html = re.sub(r'(?m)<!--.*?--\s*>', '', html)
        html = re.sub(r'(?i)<ref[^>]*>[^>]*<\/ ?ref>', '', html)
        html = re.sub(r'(?m)<.*?>', '', html)
        html = re.sub(r'(?i)&amp;', '&', html)
        
        return html
    
    def punctuate(self, text):
        """
        Convert every text part into well-formed one-space
        separate paragraph.
        """
        text = re.sub(r'\r\n|\n|\r', '\n', text)
        text = re.sub(r'\n\n+', '\n\n', text)
        
        parts = text.split('\n\n')
        partsParsed = []
        
        for part in parts:
            part = part.strip()
            
            if len(part) == 0:
                continue
            
            partsParsed.append(part)
        
        return '\n\n'.join(partsParsed)

    def get_summary(self,text):
        text = text[:text.find('==')]
        return text

    def image(self):
        url_image = 'http://simple.wikipedia.org/w/index.php?title=Special:FilePath&file=' 
        """
        Retrieve the first image in the document.
        """
        # match = re.search(r'(?i)\|?\s*(image|img|image_flag)\s*=\s*(<!--.*-->)?\s*([^\\/:*?<>"|%]+\.[^\\/:*?<>"|%]{3,4})', self.wiki)
        match = re.search(r'= (\b[\w ]+\b)+.(gif|jpg|jpeg|png|bmp)', self.wiki_article)
        if match:
            image_url = url_image + '%s.%s' % match.groups()
            image_url = re.sub(' ', '_', image_url)
            return image_url
        
        return None