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47 lines
1.7 KiB
Python
47 lines
1.7 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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# Constraints ending in "?" are optional, matching one or no word.
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# Pattern.search() uses a "greedy" approach:
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# it will attempt to include as many optional constraints as possible.
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# The following pattern scans for words whose part-of-speech tag is NN (i.e. nouns).
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# A preceding adjective, adverb or determiner are picked up as well.
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for s in (
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"the cat", # DT NN
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"the very black cat", # DT RB JJ NN
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"tasty cat food", # JJ NN NN
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"the funny black cat", # JJ NN
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"very funny", # RB JJ => no match, since there is no noun.
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"my cat is black and your cat is white"): # NN + NN
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t = parsetree(s)
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m = search("DT? RB? JJ? NN+", t)
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print("")
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print(t)
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print(m)
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if m:
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for w in m[0].words:
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print("%s matches %s" % (w, m[0].constraint(w)))
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# Before Pattern 2.4, "( )" was used instead of "?".
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# For example: "(JJ)" instead of "JJ?".
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# The syntax was changed to resemble regular expressions, which use "?".
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# The old syntax "(JJ)" still works in Pattern 2.4, but it may change later.
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# Note: the above pattern could also be written as "DT|RB|JJ?+ NN+"
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# to include multiple adverbs/adjectives.
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# By combining "*", "?" and "+" patterns can become quite complex.
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# Optional constraints are useful for very specific patterns, but slow.
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# Also, depending on which parser you use (e.g. MBSP), words can be tagged differently
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# and may not match in the way you expect.
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# Consider using a simple, robust "NP" search pattern.
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