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wikipedia dump parser and mediawiki format regex cleanup
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@ -3,6 +3,7 @@ from __future__ import unicode_literals
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"""Demonstrate how to build a knowledge base from WikiData and run an Entity Linking algorithm.
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"""
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import re
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import json
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import spacy
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import bz2
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@ -11,7 +12,8 @@ from spacy.kb import KnowledgeBase
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def create_kb(vocab):
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kb = KnowledgeBase(vocab=vocab)
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_read_wikidata()
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# _read_wikidata()
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_read_wikipedia()
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# adding entities
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# kb.add_entity(entity=entity, prob=prob)
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@ -89,6 +91,83 @@ def _read_wikidata():
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cnt += 1
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def _read_wikipedia():
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""" Read the XML wikipedia data """
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# TODO remove hardcoded path
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# with bz2.open('C:/Users/Sofie/Documents/data/wikipedia/enwiki-20190320-pages-articles-multistream-index.txt.bz2', mode='rb') as file:
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with bz2.open('C:/Users/Sofie/Documents/data/wikipedia/enwiki-20190320-pages-articles-multistream.xml.bz2', mode='rb') as file:
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line = file.readline()
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cnt = 1
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article_text = ""
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article_title = None
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article_id = None
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reading_text = False
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while line and cnt < 10000:
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clean_line = line.strip().decode("utf-8")
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# Start reading new page
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if clean_line == "<page>":
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article_text = ""
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article_title = None
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article_id = 342
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# finished reading this page
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elif clean_line == "</page>":
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if article_id:
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_store_wp_article(article_id, article_title, article_text.strip())
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# start reading text within a page
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if "<text" in clean_line:
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reading_text = True
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if reading_text:
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article_text += " " + clean_line
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# stop reading text within a page
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if "</text" in clean_line:
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reading_text = False
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# read the ID of this article
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ids = re.findall(r"(?<=<id>)\d*(?=</id>)", clean_line)
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if ids:
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article_id = ids[0]
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# read the title of this article
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titles = re.findall(r"(?<=<title>).*(?=</title>)", clean_line)
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if titles:
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article_title = titles[0].strip()
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line = file.readline()
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cnt += 1
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def _store_wp_article(article_id, article_title, article_text):
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print("WP article", article_id, ":", article_title)
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print(article_text)
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print(_get_clean_wp_text(article_text))
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print()
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def _get_clean_wp_text(article_text):
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# remove category statements
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clean_text = re.sub('\[\[Category:.*\]\]', '', article_text)
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# remove nested {{info}} statements by removing the inner/smallest ones first and iterating
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try_again = True
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previous_length = len(clean_text)
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while try_again:
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clean_text = re.sub('{[^{]*?}', '', clean_text) # non-greedy match
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print(clean_text)
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if len(clean_text) < previous_length:
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try_again = True
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else:
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try_again = False
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previous_length = len(clean_text)
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return clean_text
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def add_el(kb, nlp):
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el_pipe = nlp.create_pipe(name='entity_linker', config={"kb": kb})
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nlp.add_pipe(el_pipe, last=True)
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