Multilingual Aliasing for Auto-Generating Proposition Banks

Alan Akbik, Xinyu Guan, Yunyao Li


Abstract
Semantic Role Labeling (SRL) is the task of identifying the predicate-argument structure in sentences with semantic frame and role labels. For the English language, the Proposition Bank provides both a lexicon of all possible semantic frames and large amounts of labeled training data. In order to expand SRL beyond English, previous work investigated automatic approaches based on parallel corpora to automatically generate Proposition Banks for new target languages (TLs). However, this approach heuristically produces the frame lexicon from word alignments, leading to a range of lexicon-level errors and inconsistencies. To address these issues, we propose to manually alias TL verbs to existing English frames. For instance, the German verb drehen may evoke several meanings, including “turn something” and “film something”. Accordingly, we alias the former to the frame TURN.01 and the latter to a group of frames that includes FILM.01 and SHOOT.03. We execute a large-scale manual aliasing effort for three target languages and apply the new lexicons to automatically generate large Proposition Banks for Chinese, French and German with manually curated frames. We present a detailed evaluation in which we find that our proposed approach significantly increases the quality and consistency of the generated Proposition Banks. We release these resources to the research community.
Anthology ID:
C16-1327
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
3466–3474
Language:
URL:
https://aclanthology.org/C16-1327
DOI:
Bibkey:
Cite (ACL):
Alan Akbik, Xinyu Guan, and Yunyao Li. 2016. Multilingual Aliasing for Auto-Generating Proposition Banks. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 3466–3474, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Multilingual Aliasing for Auto-Generating Proposition Banks (Akbik et al., COLING 2016)
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PDF:
https://aclanthology.org/C16-1327.pdf