Frame Shift Prediction

Zheng Xin Yong, Patrick D. Watson, Tiago Timponi Torrent, Oliver Czulo, Collin Baker


Abstract
Frame shift is a cross-linguistic phenomenon in translation which results in corresponding pairs of linguistic material evoking different frames. The ability to predict frame shifts would enable (semi-)automatic creation of multilingual frame annotations and thus speeding up FrameNet creation through annotation projection. Here, we first characterize how frame shifts result from other linguistic divergences such as translational divergences and construal differences. Our analysis also shows that many pairs of frames in frame shifts are multi-hop away from each other in Berkeley FrameNet’s net-like configuration. Then, we propose the Frame Shift Prediction task and demonstrate that our graph attention networks, combined with auxiliary training, can learn cross-linguistic frame-to-frame correspondence and predict frame shifts.
Anthology ID:
2022.lrec-1.103
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
976–986
Language:
URL:
https://aclanthology.org/2022.lrec-1.103
DOI:
Bibkey:
Cite (ACL):
Zheng Xin Yong, Patrick D. Watson, Tiago Timponi Torrent, Oliver Czulo, and Collin Baker. 2022. Frame Shift Prediction. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 976–986, Marseille, France. European Language Resources Association.
Cite (Informal):
Frame Shift Prediction (Yong et al., LREC 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/2022.lrec-1.103.pdf