iSSKJr SSjrg))wordnetNc^[U5mUc[R"XS9nU(a1UVs/sH$n[UR 55U:XdM"UPM& nnU(dg[ UU4SjS9nU$s snf)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)langcp>[TRUR5R555$)N)len intersection definitionsplit)sscontexts B/home/james-whalen/.local/lib/python3.13/site-packages/nltk/wsd.pylesk..1s$G$8$89N9N9P$Q R)key)setrsynsetsstrposmax)context_sentenceambiguous_wordrrrr senser s @r leskr sn2"#G//.< '@"3rvvx=C+?2@  R E LAs !A4A4)NNeng) nltk.corpusrrrr rs 'r