Sources of Complexity in Semantic Frame Parsing for Information Extraction

Abstract : This paper describes a Semantic Frame parsing System based on sequence labeling methods, precisely BiLSTM models with highway connections, for performing information extraction on a corpus of French encyclopedic history texts annotated according to the Berkeley FrameNet formalism. The approach proposed in this study relies on an integrated sequence labeling model which jointly optimizes frame identification and semantic role segmentation and identification. The purpose of this study is to analyze the task complexity, to highlight the factors that make Semantic Frame parsing a difficult task and to provide detailed evaluations of the performance on different types of frames and sentences.
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Communication dans un congrès
International FrameNet Workshop 2018, May 2018, Miyazaki, Japan
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https://hal.archives-ouvertes.fr/hal-01731385
Contributeur : Gabriel Marzinotto <>
Soumis le : jeudi 20 décembre 2018 - 16:47:35
Dernière modification le : dimanche 23 décembre 2018 - 01:24:03

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  • HAL Id : hal-01731385, version 2
  • ARXIV : 1812.09193

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Gabriel Marzinotto, Frédéric Béchet, Géraldine Damnati, Alexis Nasr. Sources of Complexity in Semantic Frame Parsing for Information Extraction. International FrameNet Workshop 2018, May 2018, Miyazaki, Japan. 〈hal-01731385v2〉

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