Using Embeddings to Compare FrameNet Frames Across Languages

Jennifer Sikos, Sebastian Padó


Abstract
Much interest in Frame Semantics is fueled by the substantial extent of its applicability across languages. At the same time, lexicographic studies have found that the applicability of individual frames can be diminished by cross-lingual divergences regarding polysemy, syntactic valency, and lexicalization. Due to the large effort involved in manual investigations, there are so far no broad-coverage resources with “problematic” frames for any language pair. Our study investigates to what extent multilingual vector representations of frames learned from manually annotated corpora can address this need by serving as a wide coverage source for such divergences. We present a case study for the language pair English — German using the FrameNet and SALSA corpora and find that inferences can be made about cross-lingual frame applicability using a vector space model.
Anthology ID:
W18-3813
Volume:
Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Editors:
Peter Machonis, Anabela Barreiro, Kristina Kocijan, Max Silberztein
Venue:
LR4NLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
91–101
Language:
URL:
https://aclanthology.org/W18-3813
DOI:
Bibkey:
Cite (ACL):
Jennifer Sikos and Sebastian Padó. 2018. Using Embeddings to Compare FrameNet Frames Across Languages. In Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing, pages 91–101, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Using Embeddings to Compare FrameNet Frames Across Languages (Sikos & Padó, LR4NLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-3813.pdf
Data
FrameNet