Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study

Elior Sulem; Omri Abend; Ari Rappoport

doi:10.18653/v1/W15-3502

Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study

Elior Sulem, Omri Abend, Ari Rappoport

The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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
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	https://doi.org/10.18653/v1/W15-3502
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)
Country/Territory	China
City	Beijing
Period	30/07/15 → 30/07/15
Internet address	https://aclanthology.org/volumes/W15-35/

Keywords

MT
Machine Translation
UCCA
linguistic structure
semantic annotations
semantic structures

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10.18653/v1/W15-3502License: CC BY-NC-SA

Cite this

Sulem, E., Abend, O., & Rappoport, A. (2015). Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study. In D. Xiong, K. Duh, C. Hardmeier, & R. Navigli (Eds.), Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015) (pp. 11-22). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/W15-3502

Sulem, Elior ; Abend, Omri ; Rappoport, Ari. / Conceptual Annotations Preserve Structure Across Translations : A French-English Case Study. Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015). editor / Deyi Xiong ; Kevin Duh ; Christian Hardmeier ; Roberto Navigli. Beijing, China : Association for Computational Linguistics (ACL), 2015. pp. 11-22

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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.",

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booktitle = "Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015)",

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Sulem, E , Abend, O & Rappoport, A 2015, Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study. in D Xiong, K Duh, C Hardmeier & R Navigli (eds), Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015). Association for Computational Linguistics (ACL), Beijing, China, pp. 11-22, 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015), Beijing, China, 30/07/15. https://doi.org/10.18653/v1/W15-3502

Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study. / Sulem, Elior ; Abend, Omri ; Rappoport, Ari.
Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015). ed. / Deyi Xiong; Kevin Duh; Christian Hardmeier; Roberto Navigli. Beijing, China: Association for Computational Linguistics (ACL), 2015. p. 11-22.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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KW - UCCA

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KW - semantic annotations

KW - semantic structures

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A2 - Xiong, Deyi

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Sulem E , Abend O , Rappoport A. Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study. In Xiong D, Duh K, Hardmeier C, Navigli R, editors, Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015). Beijing, China: Association for Computational Linguistics (ACL). 2015. p. 11-22 doi: 10.18653/v1/W15-3502

Conceptual Annotations Preserve Structure Across Translations: A French-English Case Study

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Workshop

Keywords

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