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51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
5 years ago
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from __future__ import print_function
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from __future__ import unicode_literals
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from builtins import str, bytes, dict, int
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import os
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import sys
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
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from pattern.search import search
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from pattern.en import parsetree
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# The pattern.search module contains a number of pattern matching tools
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# to search a string syntactically (word function) or semantically (word meaning).
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# If you only need to match string characters, regular expressions are faster.
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# However, if you are scanning a sentence for concept types (e.g. all flowers)
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# or parts-of-speech (e.g. all adjectives), this module provides the functionality.
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# In the simplest case, the search() function
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# takes a word (or a sequence of words) that you want to retrieve:
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print(search("rabbit", "big white rabbit"))
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print("")
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# Search words can contain wildcard characters:
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print(search("rabbit*", "big white rabbit"))
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print(search("rabbit*", "big white rabbits"))
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print("")
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# Search words can contain different options:
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print(search("rabbit|cony|bunny", "big black bunny"))
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print("")
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# Things become more interesting if we involve the pattern.en.parser module.
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# The parser takes a string, identifies words, and assigns a part-of-speech tag
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# to each word, for example NN (noun) or JJ (adjective).
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# A parsed sentence can be scanned for part-of-speech tags:
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s = parsetree("big white rabbit")
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print(search("JJ", s)) # all adjectives
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print(search("NN", s)) # all nouns
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print(search("NP", s)) # all noun phrases
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print("")
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# Since the search() is case-insensitive, uppercase search words
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# are always considered to be tags (or taxonomy terms - see further examples).
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# The return value is a Match object,
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# where Match.words is a list of Word objects that matched:
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m = search("NP", s)
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for word in m[0].words:
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print(word.string, word.tag)
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