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Scientific Relation Extraction with Selectively Incorporated Concept Embeddings

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 نشر من قبل Yi Luan
 تاريخ النشر 2018
  مجال البحث الهندسة المعلوماتية
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This paper describes our submission for the SemEval 2018 Task 7 shared task on semantic relation extraction and classification in scientific papers. We extend the end-to-end relation extraction model of (Miwa and Bansal) with enhancements such as a character-level encoding attention mechanism on selecting pretrained concept candidate embeddings. Our official submission ranked the second in relation classification task (Subtask 1.1 and Subtask 2 Senerio 2), and the first in the relation extraction task (Subtask 2 Scenario 1).

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