A crowdsourced frame disambiguation corpus with ambiguity

Anca Dumitrache, Lora Aroyo, Chris Welty

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

We present a resource for the task of FrameNet semantic frame disambiguation of over 5,000 word-sentence pairs from the Wikipedia corpus. The annotations were collected using a novel crowdsourcing approach with multiple workers per sentence to capture inter-annotator disagreement. In contrast to the typical approach of attributing the best single frame to each word, we provide a list of frames with disagreement-based scores that express the confidence with which each frame applies to the word. This is based on the idea that inter-annotator disagreement is at least partly caused by ambiguity that is inherent to the text and frames. We have found many examples where the semantics of individual frames overlap sufficiently to make them acceptable alternatives for interpreting a sentence. We have argued that ignoring this ambiguity creates an overly arbitrary target for training and evaluating natural language processing systems - if humans cannot agree, why would we expect the correct answer from a machine to be any different? To process this data we also utilized an expanded lemma-set provided by the Framester system, which merges FN with WordNet to enhance coverage. Our dataset includes annotations of 1,000 sentence-word pairs whose lemmas are not part of FN. Finally we present metrics for evaluating frame disambiguation systems that account for ambiguity.

Original languageEnglish
Title of host publicationProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Subtitle of host publicationVolume 1 (Long and Short Papers)
PublisherAssociation for Computational Linguistics (ACL)
ChapterN19-1224
Pages2164-2170
Number of pages7
Volume1
ISBN (Electronic)9781950737130
DOIs
Publication statusPublished - Jun 2019
Event2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States
Duration: 2 Jun 20197 Jun 2019

Conference

Conference2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
CountryUnited States
CityMinneapolis
Period2/06/197/06/19

Fingerprint Dive into the research topics of 'A crowdsourced frame disambiguation corpus with ambiguity'. Together they form a unique fingerprint.

  • Cite this

    Dumitrache, A., Aroyo, L., & Welty, C. (2019). A crowdsourced frame disambiguation corpus with ambiguity. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Volume 1 (Long and Short Papers) (Vol. 1, pp. 2164-2170). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/N19-1224