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Adapting Semantic Role Labeling to New Genres and Languages

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AQVCBZPL3" target="_blank" >RIV/00216208:11320/23:QVCBZPL3 - isvavai.cz</a>

  • Result on the web

    <a href="https://search.proquest.com/openview/4bdae04f5b54b54f89965842b15bc309/1?pq-origsite=gscholar&cbl=18750&diss=y" target="_blank" >https://search.proquest.com/openview/4bdae04f5b54b54f89965842b15bc309/1?pq-origsite=gscholar&cbl=18750&diss=y</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    portugalština

  • Original language name

    Adapting Semantic Role Labeling to New Genres and Languages

  • Original language description

    "Semantic role labeling (SRL) is the identification of semantic predicates and their participants within a sentence, which is vital for deeper natural language understanding. State-of-the-art SRLnmodels require annotated text for training, but those annotations don’t exist for many languages and domains. The ability to annotate new corpora is hampered by limited time and budget. We explore two different ways of reducing the annotation required to produce SRL systems for new domains or languages: active learning and annotation projection."

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • 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

    2023

  • Confidentiality

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