HUJI-KU at MRP 2020: Two Transition-based Neural Parsers
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Dokumenter
- OA-HUJI-KU at MRP 2020
Forlagets udgivne version, 2,2 MB, PDF-dokument
This paper describes the HUJI-KU system submission to the shared task on CrossFramework Meaning Representation Parsing (MRP) at the 2020 Conference for Computational Language Learning (CoNLL), employing TUPA and the HIT-SCIR parser, which were, respectively, the baseline system and winning system in the 2019 MRP shared task. Both are transition-based parsers using BERT contextualized embeddings. We generalized TUPA to support the newly-added MRP frameworks and languages, and experimented with multitask learning with the HIT-SCIR parser. We reached 4th place in both the crossframework and cross-lingual tracks.
Originalsprog | Engelsk |
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Titel | Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing |
Forlag | Association for Computational Linguistics |
Publikationsdato | 2020 |
Sider | 73-82 |
DOI | |
Status | Udgivet - 2020 |
Begivenhed | CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, - Onlinr Varighed: 19 nov. 2020 → 20 nov. 2020 |
Konference
Konference | CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, |
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Lokation | Onlinr |
Periode | 19/11/2020 → 20/11/2020 |
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