Wide-Coverage Neural A* Parsing for Minimalist Grammars

John Torr, Miloš Stanojević, Mark Steedman, Shay B. Cohen


Abstract
Minimalist Grammars (Stabler, 1997) are a computationally oriented, and rigorous formalisation of many aspects of Chomsky’s (1995) Minimalist Program. This paper presents the first ever application of this formalism to the task of realistic wide-coverage parsing. The parser uses a linguistically expressive yet highly constrained grammar, together with an adaptation of the A* search algorithm currently used in CCG parsing (Lewis and Steedman, 2014; Lewis et al., 2016), with supertag probabilities provided by a bi-LSTM neural network supertagger trained on MGbank, a corpus of MG derivation trees. We report on some promising initial experimental results for overall dependency recovery as well as on the recovery of certain unbounded long distance dependencies. Finally, although like other MG parsers, ours has a high order polynomial worst case time complexity, we show that in practice its expected time complexity is cubic in the length of the sentence. The parser is publicly available.
Anthology ID:
P19-1238
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Anna Korhonen, David Traum, Lluís Màrquez
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2486–2505
Language:
URL:
https://aclanthology.org/P19-1238
DOI:
10.18653/v1/P19-1238
Bibkey:
Cite (ACL):
John Torr, Miloš Stanojević, Mark Steedman, and Shay B. Cohen. 2019. Wide-Coverage Neural A* Parsing for Minimalist Grammars. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2486–2505, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Wide-Coverage Neural A* Parsing for Minimalist Grammars (Torr et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-1238.pdf