COMBINED APPROACH TO HYPERNYM DETECTION FOR THESAURUS ENRICHMENT
Mikhail Tikhomirov, Natalia Loukachevitch, Ekaterina Parkhomenko · Computational Linguistics and Intellectual Technologies · 2020
This paper describes a combined approach to hypernym detection task. The approach combines the following techniques: distribution semantics, rulebased patterns, and modern neural networks (BERT). An important feature of our solution is that hypernyms are extracted only from a single text collection provided by the organizers. The described approach obtained the fourth result on the private nouns track. It was found out that the use of the rulebased patterns can significantly improve the results. Also, using the BERT model as an additional factor always helps to improve the performance.