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115 lines
4.2 KiB
Cython
115 lines
4.2 KiB
Cython
'''Accessors for Lexeme properties, given a lex_id, which is cast to a Lexeme*.
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Mostly useful from Python-space. From Cython-space, you can just cast to
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Lexeme* yourself.
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'''
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cpdef StringHash sic_of(size_t lex_id) except 0:
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'''Access the `sic' field of the Lexeme pointed to by lex_id.
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The sic field stores the hash of the whitespace-delimited string-chunk used to
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construct the Lexeme.
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>>> [unhash(sic_of(lex_id)) for lex_id in from_string(u'Hi! world')]
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[u'Hi!', u'', u'world]
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'''
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return (<Lexeme*>lex_id).sic
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cpdef StringHash lex_of(size_t lex_id) except 0:
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'''Access the `lex' field of the Lexeme pointed to by lex_id.
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The lex field is the hash of the string you would expect to get back from
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a standard tokenizer, i.e. the word with punctuation and other non-whitespace
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delimited tokens split off. The other fields refer to properties of the
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string that the lex field stores a hash of, except sic and tail.
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>>> [unhash(lex_of(lex_id) for lex_id in from_string(u'Hi! world')]
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[u'Hi', u'!', u'world']
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'''
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return (<Lexeme*>lex_id).lex
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cpdef ClusterID cluster_of(size_t lex_id):
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'''Access the `cluster' field of the Lexeme pointed to by lex_id, which
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gives an integer representation of the cluster ID of the word,
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which should be understood as a binary address:
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>>> strings = (u'pineapple', u'apple', u'dapple', u'scalable')
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>>> token_ids = [lookup(s) for s in strings]
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>>> clusters = [cluster_of(t) for t in token_ids]
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>>> print ["{0:b"} % cluster_of(t) for t in token_ids]
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["100111110110", "100111100100", "01010111011001", "100111110110"]
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The clusterings are unideal, but often slightly useful.
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"pineapple" and "apple" share a long prefix, indicating a similar meaning,
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while "dapple" is totally different. On the other hand, "scalable" receives
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the same cluster ID as "pineapple", which is not what we'd like.
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'''
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return (<Lexeme*>lex_id).cluster
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cpdef Py_UNICODE first_of(size_t lex_id):
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'''Access the `first' field of the Lexeme pointed to by lex_id, which
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stores the first character of the lex string of the word.
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>>> lex_id = lookup(u'Hello')
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>>> unhash(first_of(lex_id))
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u'H'
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'''
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return (<Lexeme*>lex_id).first
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cpdef double prob_of(size_t lex_id):
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'''Access the `prob' field of the Lexeme pointed to by lex_id, which stores
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the smoothed unigram log probability of the word, as estimated from a large
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text corpus. By default, probabilities are based on counts from Gigaword,
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smoothed using Knesser-Ney; but any probabilities file can be supplied to
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load_probs.
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>>> prob_of(lookup(u'world'))
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-20.10340371976182
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'''
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pass
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cpdef StringHash last3_of(size_t lex_id):
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'''Access the `last3' field of the Lexeme pointed to by lex_id, which stores
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the hash of the last three characters of the word:
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>>> lex_ids = [lookup(w) for w in (u'Hello', u'!')]
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>>> [unhash(last3_of(lex_id)) for lex_id in lex_ids]
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[u'llo', u'!']
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'''
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return (<Lexeme*>lex_id).last3
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cpdef bint is_oft_upper(size_t lex_id):
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'''Access the `oft_upper' field of the Lexeme pointed to by lex_id, which
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stores whether the lowered version of the string hashed by `lex' is found
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in all-upper case frequently in a large sample of text. Users are free
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to load different data, by default we use a sample from Wikipedia, with
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a threshold of 0.95, picked to maximize mutual information for POS tagging.
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>>> is_oft_upper(lookup(u'abc'))
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True
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>>> is_oft_upper(lookup(u'aBc')) # This must get the same answer
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True
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'''
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return (<Lexeme*>lex_id).oft_upper
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cpdef bint is_oft_title(size_t lex_id):
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'''Access the `oft_upper' field of the Lexeme pointed to by lex_id, which
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stores whether the lowered version of the string hashed by `lex' is found
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title-cased frequently in a large sample of text. Users are free
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to load different data, by default we use a sample from Wikipedia, with
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a threshold of 0.3, picked to maximize mutual information for POS tagging.
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>>> is_oft_title(lookup(u'marcus'))
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True
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>>> is_oft_title(lookup(u'MARCUS')) # This must get the same value
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True
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'''
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return (<Lexeme*>lex_id).oft_title
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