Papers with Frame semantic parsing

2 papers
A Graph-Based Neural Model for End-to-End Frame Semantic Parsing (2021.emnlp-main)

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Challenge: Existing studies focus on frame semantic parsing as a graph construction problem.
Approach: They propose an end-to-end neural model to tackle frame semantic parsing jointly.
Outcome: The proposed model is highly competitive and performs better than pipeline models on two benchmark datasets.
A Double-Graph Based Framework for Frame Semantic Parsing (2022.naacl-main)

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Challenge: Frame semantic parsing is a fundamental NLP task, which consists of three subtasks: frame identification, argument identification and role classification.
Approach: They propose a frame semantic parser with a double-graph to derive knowledge-enhanced representations for frames and FEs.
Outcome: The proposed method outperforms the state-of-the-art method by up to 1.7 F1-score on two FrameNet datasets.

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