Generating Text from Uniform Meaning Representation

• URL: http://arxiv.org/abs/2502.11973v1
• Date: Mon, 17 Feb 2025 16:20:22 GMT
• Title: Generating Text from Uniform Meaning Representation
• Abstract summary: Uniform Meaning Representation (UMR) is a graph-based semantic representation.<n>Efforts must be placed toward developing a UMR technological ecosystem.<n>We investigate the first approaches to producing text from multilingual UMR graphs.
• Score: 3.031375888004876
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Uniform Meaning Representation (UMR) is a recently developed graph-based semantic representation, which expands on Abstract Meaning Representation (AMR) in a number of ways, in particular through the inclusion of document-level information and multilingual flexibility. In order to effectively adopt and leverage UMR for downstream tasks, efforts must be placed toward developing a UMR technological ecosystem. Though still limited amounts of UMR annotations have been produced to date, in this work, we investigate the first approaches to producing text from multilingual UMR graphs: (1) a pipeline conversion of UMR to AMR, then using AMR-to-text generation models, (2) fine-tuning large language models with UMR data, and (3) fine-tuning existing AMR-to-text generation models with UMR data. Our best performing model achieves a multilingual BERTscore of 0.825 for English and 0.882 for Chinese when compared to the reference, which is a promising indication of the effectiveness of fine-tuning approaches for UMR-to-text generation with even limited amounts of UMR data.

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