Abstract
We describe the TRAPACC system and its variant TRAPACCS that participated in the closed track of the PARSEME Shared Task 2018 on labeling verbal multiword expressions (VMWEs). TRAPACC is a modified arc-standard transition system based on Constant and Nivre’s (2016) model of joint syntactic and lexical analysis in which the oracle is approximated using a classifier. For TRAPACC, the classifier consists of a data-independent dimension reduction and a convolutional neural network (CNN) for learning and labelling transitions. TRAPACCS extends TRAPACC by replacing the softmax layer of the CNN with a support vector machine (SVM). We report the results obtained for 19 languages, for 8 of which our system yields the best results compared to other participating systems in the closed-track of the shared task.- Anthology ID:
- W18-4930
- Volume:
- Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Agata Savary, Carlos Ramisch, Jena D. Hwang, Nathan Schneider, Melanie Andresen, Sameer Pradhan, Miriam R. L. Petruck
- Venues:
- LAW | MWE
- SIGs:
- SIGLEX | SIGANN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 268–274
- Language:
- URL:
- https://aclanthology.org/W18-4930
- DOI:
- Cite (ACL):
- Regina Stodden, Behrang QasemiZadeh, and Laura Kallmeyer. 2018. TRAPACC and TRAPACCS at PARSEME Shared Task 2018: Neural Transition Tagging of Verbal Multiword Expressions. In Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018), pages 268–274, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- TRAPACC and TRAPACCS at PARSEME Shared Task 2018: Neural Transition Tagging of Verbal Multiword Expressions (Stodden et al., LAW-MWE 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/W18-4930.pdf