dc.contributor.author |
Tikhomirov M.M. |
|
dc.contributor.author |
Loukachevitch N.V. |
|
dc.contributor.author |
Parkhomenko E.A. |
|
dc.date.accessioned |
2021-02-25T07:01:55Z |
|
dc.date.available |
2021-02-25T07:01:55Z |
|
dc.date.issued |
2020 |
|
dc.identifier.issn |
2221-7932 |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/161618 |
|
dc.description.abstract |
© 2020 ABBYY PRODUCTION LLC. All rights reserved. This paper describes a combined approach to hypernym detection task. The approach combines the following techniques: distribution semantics, rule-based 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 rule-based patterns can significantly improve the results. Also, using the BERT model as an additional factor always helps to improve the performance. |
|
dc.relation.ispartofseries |
Komp'juternaja Lingvistika i Intellektual'nye Tehnologii |
|
dc.subject |
BERT |
|
dc.subject |
Embeddings |
|
dc.subject |
Hypernym extraction |
|
dc.subject |
Patterns |
|
dc.subject |
Thesaurus |
|
dc.title |
Combined approach to hypernym detection for thesaurus enrichment |
|
dc.type |
Conference Paper |
|
dc.relation.ispartofseries-issue |
19 |
|
dc.relation.ispartofseries-volume |
2020-June |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
736 |
|
dc.source.id |
SCOPUS22217932-2020-2020-19-SID85093869167 |
|