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This script allows to extract proper nouns from an English text with NTLK. Install dependencies -------------------- * Install NTLK according your OS (pkg install ntlk on FreeBSD for example) * Install numpy (pkg install py27-numpy) * Download the needed NLTK resources with ntlk.download(): ** averaged_perceptron_tagger ** maxent_treebank_pos_tagger ** punkt ** treebank Source text ----------- You need a copy of the text you want to extract from as plain text. Source English word list ------------------------ The expected format is a list in lowercase, each line a substantive word. Filename should be wordsEn.txt or modified in eliminate-common-nouns script. Such file was available at [SIL](http://web.archive.org/web/20141122213941/http://www-01.sil.org/linguistics/wordlists/english/). Usage ----- ./extract-proper-nouns source.txt > nouns.txt To sort them and eliminate duplicates: ./extract-proper-nouns source.txt | sort | uniq > nouns.txt To discard known English words: ./eliminate-common-nouns nouns.txt Acknowledgment -------------- Thank you to Rama for NLTK suggestion and some brief guidance. The original code idea is from Alvations, and could be seen at http://stackoverflow.com/a/17672491/1930997.
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Extract proper nouns from an English text with NLTK POS tagging
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