Cross-lingual Decompositional Semantic Parsing

Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, Benjamin Van Durme


Abstract
We introduce the task of cross-lingual decompositional semantic parsing: mapping content provided in a source language into a decompositional semantic analysis based on a target language. We present: (1) a form of decompositional semantic analysis designed to allow systems to target varying levels of structural complexity (shallow to deep analysis), (2) an evaluation metric to measure the similarity between system output and reference semantic analysis, (3) an end-to-end model with a novel annotating mechanism that supports intra-sentential coreference, and (4) an evaluation dataset on which our model outperforms strong baselines by at least 1.75 F1 score.
Anthology ID:
D18-1194
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1664–1675
Language:
URL:
https://aclanthology.org/D18-1194
DOI:
10.18653/v1/D18-1194
Bibkey:
Cite (ACL):
Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2018. Cross-lingual Decompositional Semantic Parsing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1664–1675, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Cross-lingual Decompositional Semantic Parsing (Zhang et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/D18-1194.pdf
Attachment:
 D18-1194.Attachment.pdf