Abstract
Divergence of syntactic structures between languages constitutes a major challenge in using linguistic structure in Machine Translation (MT) systems. Here, we examine the potential of semantic structures. While semantic annotation is appealing as a source of cross-linguistically stable structures, little has been accomplished in demonstrating this stability through a detailed corpus study. In this paper, we experiment with the UCCA conceptual-cognitive annotation scheme in an English-French case study. First, we show that UCCA can be used to annotate French, through a systematic type-level analysis of the major French grammatical phenomena. Second, we annotate a parallel English-French corpus with UCCA, and quantify the similarity of the structures on both sides. Results show a high degree of stability across translations, supporting the usage of semantic annotations over syntactic ones in structure-aware MT systems.
Original language | English |
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Title of host publication | Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015) |
Editors | Deyi Xiong, Kevin Duh, Christian Hardmeier, Roberto Navigli |
Place of Publication | Beijing, China |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 11-22 |
Number of pages | 12 |
ISBN (Electronic) | 978-1-941643-61-7 |
DOIs | |
State | Published - 1 Jul 2015 |
Event | 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015) - Beijing, China Duration: 30 Jul 2015 → 30 Jul 2015 Conference number: 1 https://aclanthology.org/volumes/W15-35/ |
Workshop
Workshop | 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015) |
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Country/Territory | China |
City | Beijing |
Period | 30/07/15 → 30/07/15 |
Internet address |
Keywords
- linguistic structure
- Machine Translation
- MT
- semantic structures
- UCCA
- semantic annotations