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Exploring the Dissociated Nucleus Phenomenon in Semantic Role Labeling

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AKYN2XKB9" target="_blank" >RIV/00216208:11320/25:KYN2XKB9 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214410230&partnerID=40&md5=f1498691347db27ad224f407b5ba34f4" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214410230&partnerID=40&md5=f1498691347db27ad224f407b5ba34f4</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring the Dissociated Nucleus Phenomenon in Semantic Role Labeling

  • Original language description

    Dependency-based Semantic Role Labeling (SRL) is bound to dependency parsing, as the arguments of a predicate are identified through the token that heads the dependency relation subtree of the argument span. However, dependency-based SRL corpora are susceptible to the dissociated nucleus problem: when a subclause's semantic and structural cores are two separate words, the dependency tree chooses the structural token as the head of the subtree, coercing the SRL annotation into making the same choice. This leads to undesirable consequences: when directly using the output of a dependency-based SRL method in downstream tasks it is useful to work with the token representing the semantic core of a subclause, not the structural core. In this paper, we carry out a linguistically-driven investigation on the dissociated nucleus problem in dependency-based SRL and propose a novel algorithm that aligns predicate-argument structures to the syntactic structures from Universal Dependencies to select the semantic core of an argument. Our analysis shows that dissociated nuclei appear more often than one might expect, and that our novel algorithm greatly increases the richness of the semantic information in dependency-based SRL. We release the software to reproduce our experiments at https://github.com/SapienzaNLP/semdepalign. © 2024 CEUR-WS. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    CEUR Workshop Proc.

  • ISBN

  • ISSN

    1613-0073

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    1-9

  • Publisher name

    CEUR-WS

  • Place of publication

  • Event location

    Pisa

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article