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- András Kornai, Judit Ács, Márton Makrai, Dávid Márk Nemeskey, Katalin Pajkossy, Gábor Recski
- *SEM@NAACL-HLT
- 2015

We investigate from the competence standpoint two recent models of lexical semantics, algebraic conceptual representations and continuous vector models. Characterizing what it means for a speaker to be competent in lexical semantics remains perhaps the most significant stumbling block in reconciling the two main threads of semantics, Chomsky’s cognitivism… (More)

We introduce a new 50-dimensional embedding obtained by spectral clustering of a graph describing the conceptual structure of the lexicon. We use the embedding directly to investigate sets of antonymic pairs, and indirectly to argue that function application in CVSMs requires not just vectors but two transformations (corresponding to subject and object) as… (More)

- Gábor Borbély, Márton Makrai, Dávid Márk Nemeskey, András Kornai
- RepEval@ACL
- 2016

Multi-sense word embeddings (MSEs) model different meanings of word forms with different vectors. We propose two new methods for evaluating MSEs, one based on monolingual dictionaries, and the other exploiting the principle that words may be ambiguous as far as the postulated senses translate to different words in some other language.

- Márton Makrai
- 2016

Triangulation infers word translations in a pair of languages based on translations to other, typically better resourced ones called pivots. This method may introduce noise if words in the pivot are polysemous. The reliability of each triangulated translation is basically estimated by the number of pivot languages (Tanaka and Umemura, 1994). Mikolov et al.… (More)

- Márton Makrai
- LREC
- 2016

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