jddlmZddZdS))wordnetNengct||tj||}rfd|D}|sdSt|fd}|S)aReturn a synset for an ambiguous word in a context. :param iter context_sentence: The context sentence where the ambiguous word occurs, passed as an iterable of words. :param str ambiguous_word: The ambiguous word that requires WSD. :param str pos: A specified Part-of-Speech (POS). :param iter synsets: Possible synsets of the ambiguous word. :param str lang: WordNet language. :return: ``lesk_sense`` The Synset() object with the highest signature overlaps. This function is an implementation of the original Lesk algorithm (1986) [1]. Usage example:: >>> lesk(['I', 'went', 'to', 'the', 'bank', 'to', 'deposit', 'money', '.'], 'bank', 'n') Synset('depository_financial_institution.n.01') [1] Lesk, Michael. "Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone." Proceedings of the 5th Annual International Conference on Systems Documentation. ACM, 1986. https://dl.acm.org/citation.cfm?id=318728 N)langc^g|])}t|k'|*S)strpos).0ssr s k/home/lighthouse/badge-speaker-benchmark/.benchmark-venv-community/lib/python3.11/site-packages/nltk/wsd.py zlesk..+s1@@@"3rvvxx==C+?+?2+?+?+?ct|S)N)len intersection definitionsplit)r contexts r zlesk..1s1G$8$89N9N9P9P$Q$Q R Rr)key)setrsynsetsmax)context_sentenceambiguous_wordr rrsensers ` @r leskr s2"##G/.t<<< A@@@@@@@ t RRRR   E Lr)NNr) nltk.corpusrrrrr r s7 ''''''r