Semantic textual similarity es-en wmt

Semantic Textual Similarity measures the meaning similarity of sentences. This task aims at investigating  the relationship between Semantic Textual Similarity  and Machine Translation quality estimation by providing Semantic Textual Similarity labels for the Workshop on Machine Translation 2014 quality estimation data. The data includes Spanish translations of English sentences from a variety of methods including RBMT, SMT, hybrid-MT and human translation. Systems need to compare Spanish and English sentences.

Publication
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017. SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 1–14, Vancouver, Canada. Association for Computational Linguistics.
Competition
SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation
Language
Spanish
English
NLP topic
text similarity
Abstract task
Correlation
Dataset
STS 2017-es-en-WMT
Year
2017
Publication link
https://aclanthology.org/S17-…

Task results

System Pearson correlation
SEF@UHH 0.3407
ECNU 0.3363
ECNU 0.3311
SEF@UHH 0.3069
ECNU 0.2633

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.