/hSSKJr SSjrg))wordnetNc^[U5mUc[R"XS9nU(a1UVs/sH$n[UR 55U:XdM"UPM& nnU(dg[ U4SjU55upgU$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('savings_bank.n.02') [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)langc3># UH=n[TRUR5R555U4v M? g7f)N)len intersection definitionsplit).0sscontexts @/var/www/auris/envauris/lib/python3.13/site-packages/nltk/wsd.py lesk..0s8KRRW ! !"--/"7"7"9 : ;R@7sAA)setrsynsetsstrposmax) context_sentenceambiguous_wordrrrr _senser s @rleskr sw2"#G//.< '@"3rvvx=C+?2@ KRHA LAs !A=A=)NNeng) nltk.corpusrrrrs 'r