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The Eval4NLP Shared Task on Explainable Quality Estimation: Overview and Results

Marina Fomicheva, Piyawat Lertvittayakumjorn, Wei Zhao, Steffen Eger, Yang Gao

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Abstract

In this paper, we introduce the Eval4NLP-2021 shared task on explainable quality estimation. Given a source-translation pair, this shared task requires not only to provide a sentencelevel score indicating the overall quality of the translation, but also to explain this score by identifying the words that negatively impact translation quality. We present the data, annotation guidelines and evaluation setup of the shared task, describe the six participating systems, and analyze the results. To the best of our knowledge, this is the first shared task on explainable NLP evaluation metrics. Datasets and results are available at https://github. com/eval4nlp/SharedTask2021.

Topics & Concepts

Task (project management)Computer scienceQuality (philosophy)Machine translationNatural language processingAnnotationSentenceEstimationTranslation (biology)Artificial intelligenceTask analysisInformation retrievalBiochemistryPhilosophyGeneManagementEpistemologyMessenger RNAEconomicsChemistryTopic ModelingExplainable Artificial Intelligence (XAI)Natural Language Processing Techniques
The Eval4NLP Shared Task on Explainable Quality Estimation: Overview and Results | Litcius