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Dependency and Span, Cross-Style Semantic Role Labeling on PropBank and NomBank

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Published:12 November 2022Publication History
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Abstract

The latest developments in neural semantic role labeling (SRL) have shown great performance improvements with both the dependency and span formalism/styles. Although the two styles share many similarities in linguistic meaning and computation, most previous studies focus on a single style. In this article, we define a new cross-style semantic role label convention and propose a new cross-style joint optimization model designed around the most basic linguistic meaning of a semantic role. Our work provides a solution to make the results of the two styles more comparable and allowing both formalisms of SRL to benefit from their natural connections in both linguistics and computation. Our model learns a general semantic argument structure and is capable of outputting in either style. Additionally, we propose a syntax-aided method to uniformly enhance the learning of both dependency and span representations. Experiments show that the proposed methods are effective on both span and dependency SRL benchmarks.

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  1. Dependency and Span, Cross-Style Semantic Role Labeling on PropBank and NomBank

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    • Published in

      cover image ACM Transactions on Asian and Low-Resource Language Information Processing
      ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 21, Issue 6
      November 2022
      372 pages
      ISSN:2375-4699
      EISSN:2375-4702
      DOI:10.1145/3568970
      Issue’s Table of Contents

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      • Published: 12 November 2022
      • Online AM: 13 April 2022
      • Accepted: 12 March 2022
      • Revised: 7 December 2021
      • Received: 15 November 2020
      Published in tallip Volume 21, Issue 6

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