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