Papers with SemDP

1 papers
Leveraging Linguistically Enhanced Embeddings for Open Information Extraction (2024.lrec-main)

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Challenge: Open Information Extraction (OIE) is a structure prediction task in NLP that aims to extract structured n-ary tuples from free text.
Approach: They propose to leverage linguistic features with a Seq2Seq PLM for OIE to improve performance.
Outcome: The proposed methods give any neural OIE architecture the key performance boost from both PLMs and linguistic features in one go.

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