Papers with NomBank

2 papers
Semantic Role Labeling of NomBank Partitives (2025.coling-main)

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Challenge: Semantic role labeling (SRL) is a way to represent semantic concepts via labeled predicate/argument pairs.
Approach: They describe a semantic role labeling task that uses a set of predicate/argument pairs to represent semantic concepts.
Outcome: The highest scoring system achieves an F1 of 91.74% using “gold” parses from the Penn Treebank and 91.12% when using the Berkeley Neural parser.
Crowdsourcing Question-Answer Meaning Representations (N18-2)

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Challenge: Existing datasets for predicate-argument relationships are lacking highly skilled and trained annotators.
Approach: They propose a crowdsourcing scheme to generate question-answer pairs that represent predicate-argument relationships in sentences as a set of question-announcer pairs.
Outcome: The proposed model covers the vast majority of predicate-argument relationships in existing datasets along with many previously under-resourced ones, including implicit arguments and relations.

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