Márton Makrai
Márton Makrai conducts computational semantic research as a junior research fellow at the research institutes for Linguistics (NYI) and Cognitive Neuroscience and Psychology of the Hungarian Academy of Sciences. His main field of interest is machine learning for word ambiguity.
The Hungarian version of this page may be more clear for people who are unfamiliar with natural language processing but speak Hungarian.
Currently, he writes the last chapter of his dissertation at the MTA-ELTE theoretical linguistics program which links together his two major topics so far, verbal roles and linear algebraic models.
- the 4lang semantic network: gold meaning representations of the defining vocabulary, deep cases, spreading activation, and the defining vocabulary with IR and lexicography.
- semantic granularity of multi-sense word embeddings
- hypernyms with sparse word representations, winning some categories at the SemEval 2018 task.
- word translation combining the method of triangulation with the linear mapping of vectors -- German--Hungarian word pairs with confidence scores
- Hungarian equivalents of the analogy question set for evaluating embeddings
- young researcher 2015--2018 at MTA NYI
- master's thesis on a mathematical model of language acquisition (identification in the limit)
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