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RISS 인기검색어
- 검색키워드
- 저자 : ( Mehrnoosh Sadrzadeh ) (검색결과 2 건)
- 무료
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- 유료
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Anaphora and Ellipsis in Lambek Calculus with a Relevant Modality: Syntax and Semantics
( Lachlan Mcpheat ),( Gijs Wijnholds ),( Mehrnoosh Sadrzadeh ),( Adriana Correia ),( Alexis Toumi ) 서울대학교 인지과학연구소 2021 Journal of Cognitive Science Vol.22 No.2
Lambek calculus with a relevant modality !L* of (Kanovich et al., 2016) syntactically resolves parasitic gaps in natural language. It resembles the Lambek calculus with anaphora LA of (Jäger, 1998) and the Lambek calculus with controlled contraction L<sub>◊</sub> of (Wijnholds and Sadrzadeh, 2019b) which deal with anaphora and ellipsis. What all these calculi add to Lambek calculus is a copying and moving behaviour. Distributional semantics is a subfield of Natural Language Processing that uses vector space semantics for words via co-occurrence statistics in large corpora of data. Compositional vector space semantics for Lambek Calculi are obtained via the DisCoCat models (Coecke et al., 2010). LA does not have a vector space semantics and the semantics of L<sub>◊</sub> is not compositional. Previously, we developed a DisCoCat semantics for !L* and focused on the parasitic gap applications. In this paper, we use the vector space instance of that general semantics and show how one can also interpret anaphora, ellipsis, and for the first time derive the sloppy vs strict vector readings of ambiguous anaphora with ellipsis cases. The base of our semantics is tensor algebras and their finite dimensional variants: the Fermionic Fock spaces of Quantum Mechanics. We implement our model and experiment with the ellipsis disambiguation task of (Wijnholds and Sadrzadeh, 2019a).
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Analysing Ambiguous Nouns and Verbs with Quantum Contextuality Tools
( Daphne Wang ),( Mehrnoosh Sadrzadeh ),( Samson Abramsky ),( Víctor H. Cervantes ) 서울대학교 인지과학연구소 2021 Journal of Cognitive Science Vol.22 No.3
Psycholinguistic research uses eye-tracking to show that polysemous words are disambiguated differently from homonymous words, and that ambiguous verbs are disambiguated differently than ambiguous nouns. Research in Compositional Distributional Semantics uses cosine distances to show that verbs are disambiguated more efficiently in the context of their subjects and objects than when on their own. These two frameworks both focus on one ambiguous word at a time and neither considers ambiguous phrases with two (or more) ambiguous words. We borrow methods and measures from Quantum Information Theory, the framework of Contextuality-by-Default and degrees of contextual influences, and work with ambiguous subject-verb and verb-object phrases of English, where both the subject/object and the verb are ambiguous. We show that differences in the processing of ambiguous verbs versus ambiguous nouns, as well as between different levels of ambiguity in homonymous versus polysemous nouns and verbs can be modelled using the averages of the degrees of their contextual influences.
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