Papers by Seung-Cheol Lee

1 papers
Using Sentence-level Classification Helps Entity Extraction from Material Science Literature (2022.lrec-1)

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Challenge: Material Science research articles are a rich source of information about entities related to material science.
Approach: They propose to use a sentence-level classifier to identify sentences containing at least one entity mention . they then apply the information extraction models only on the filtered sentences to extract various entities of interest.
Outcome: The proposed model improves the F1 score by more than 4% . the proposed model removes redundant sentences from the articles that contain informative entities .

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