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Frame Shift Prediction

arXiv 2201.01837 ↗First posted 5 Jan 2022cs.CL cs.AI cs.LGcited by 0

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Abstract (arXiv)

Frame shift is a cross-linguistic phenomenon in translation which results in corresponding pairs of linguistic material evoking different frames. The ability to predict frame shifts enables automatic creation of multilingual FrameNets through annotation projection. Here, we propose the Frame Shift Prediction task and demonstrate that graph attention networks, combined with auxiliary training, can learn cross-linguistic frame-to-frame correspondence and predict frame shifts.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 18 of its 57 references that are in the map. First posted on arXiv 5 Jan 2022.

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18 of 57 references.

References · 18

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6 more
  1. 2019Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphscited by 125
  2. 2019Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsingcited by 74
  3. 2017Situation Recognition with Graph Neural Networkscited by 34
  4. 2020(Re)construing Meaning in NLPcited by 16
  5. 2018Learning Joint Semantic Parsers from Disjoint Datacited by 12
  6. 2014Cross-lingual Annotation Projection for Semantic Rolescited by 11

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