HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings

Saba Anwar, Dmitry Ustalov, Nikolay Arefyev, Simone Paolo Ponzetto, Chris Biemann, Alexander Panchenko


Abstract
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (Qasem-iZadeh et al., 2019). Our approach separates this task into two independent steps: verb clustering using word and their context embeddings and role labeling by combining these embeddings with syntactical features. A simple combination of these steps shows very competitive results and can be extended to process other datasets and languages.
Anthology ID:
S19-2018
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
125–129
Language:
URL:
https://aclanthology.org/S19-2018
DOI:
10.18653/v1/S19-2018
Bibkey:
Cite (ACL):
Saba Anwar, Dmitry Ustalov, Nikolay Arefyev, Simone Paolo Ponzetto, Chris Biemann, and Alexander Panchenko. 2019. HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 125–129, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings (Anwar et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2018.pdf
Code
 uhh-lt/semeval2019-hhmm
Data
FrameNet