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This paper presents the findings of the SIGMORPHON 2023 Shared Task on Interlinear Glossing. This first iteration of the shared task explores glossing of a set of six typologically diverse languages: Arapaho, Gitksan, Lezgi, Natügu, Tsez and Uspanteko. The shared task encompasses two tracks: a resource-scarce closed track and an open track, where participants are allowed to utilize external data resources. Five teams participated in the shared task. The winning team Tü-CL achieved a 23.99%-point improvement over a baseline RoBERTa system in the closed track and a 17.42%-point improvement in the open track.more » « less
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Moeller, Sarah; Wagner, Irina; Palmer, Martha; Conger, Kathryn; Myers, Skatje (, Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020),)This paper presents a proposition bank for Russian (RuPB), a resource for semantic role labeling (SRL). The motivating goal for this resource is to automatically project semantic role labels from English to Russian. This paper describes frame creation strategies, coverage, and the process of sense disambiguation. It discusses language-specific issues that complicated the process of building the PropBank and how these challenges were exploited as language-internal guidance for consistency and coherence.more » « less
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Van Gysel, Jens E.; Vigus, Meagan; Chun, Jayeol; Lai, Kenneth; Moeller, Sarah; Yao, Jiarui; O’Gorman, Tim; Cowell, Andrew; Croft, William; Huang, Chu-Ren; et al (, KI - Künstliche Intelligenz)null (Ed.)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.more » « less
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