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Creators/Authors contains: "Yao, Jiarui"

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  1. ; ; (, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies)
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  2. ; ; ; ; (, Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers))
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  3. ; ; ; (, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP))
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  4. ; ; ; ; ; ; ; ; ; ; et al (, KI - Künstliche Intelligenz)
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    In this paper we present Uniform Meaning Representation (UMR), a meaning representation designed to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries. 
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