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80 lines
3.0 KiB
Cython
80 lines
3.0 KiB
Cython
# cython: profile=True
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# cython: embedsignature=True
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from libc.stdlib cimport calloc, free, realloc
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cdef class Lexeme:
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"""A lexical type.
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Clients should avoid instantiating Lexemes directly, and instead use get_lexeme
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from a language module, e.g. spacy.en.get_lexeme . This allows us to use only
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one Lexeme object per lexical type.
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Attributes:
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id (view_id_t):
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A unique ID of the word's string.
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Implemented as the memory-address of the string,
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as we use Python's string interning to guarantee that only one copy
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of each string is seen.
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string (unicode):
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The unicode string.
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Implemented as a property; relatively expensive.
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length (size_t):
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The number of unicode code-points in the string.
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prob (double):
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An estimate of the word's unigram log probability.
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Probabilities are calculated from a large text corpus, and smoothed using
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simple Good-Turing. Estimates are read from data/en/probabilities, and
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can be replaced using spacy.en.load_probabilities.
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cluster (int):
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An integer representation of the word's Brown cluster.
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A Brown cluster is an address into a binary tree, which gives some (noisy)
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information about the word's distributional context.
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>>> strings = (u'pineapple', u'apple', u'dapple', u'scalable')
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>>> print ["{0:b"} % lookup(s).cluster for s in strings]
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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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def __cinit__(self, unicode string, double prob, int cluster, dict case_stats,
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dict tag_stats, list string_features, list flag_features):
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self.prob = prob
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self.cluster = cluster
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self.length = len(string)
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self.string = string
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for string_feature in string_features:
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view = string_feature(string, prob, cluster, case_stats, tag_stats)
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self.views.append(view)
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for i, flag_feature in enumerate(flag_features):
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if flag_feature(string, prob, case_stats, tag_stats):
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self.set_flag(i)
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def __dealloc__(self):
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pass
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cpdef bint check_flag(self, size_t flag_id) except *:
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"""Access the value of one of the pre-computed boolean distribution features.
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Meanings depend on the language-specific distributional features being loaded.
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The suggested features for latin-alphabet languages are: TODO
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"""
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return self.flags & (1 << flag_id)
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cpdef int set_flag(self, size_t flag_id) except -1:
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self.flags |= (1 << flag_id)
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