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A computational construction grammar approach to semantic frame extraction

  • Katrien Beuls ORCID logo EMAIL logo , Paul Van Eecke ORCID logo and Vanja Sophie Cangalovic
Published/Copyright: February 18, 2021
Linguistics Vanguard
From the journal Linguistics Vanguard Volume 7 Issue 1

Abstract

This paper introduces a novel methodology for extracting semantic frames from text corpora. Building on recent advances in computational construction grammar, the method captures expert knowledge of how semantic frames can be expressed in the form of conventionalised form-meaning pairings, called constructions. By combining these constructions in a semantic parsing process, the frame-semantic structure of a sentence is retrieved through the intermediary of its morpho-syntactic structure. The main advantage of this approach is that state-of-the-art results are achieved, without the need for annotated training data. We demonstrate the method in a case study where causation frames are extracted from English newspaper articles, and compare it to a commonly used approach based on Conditional Random Fields (CRFs). The computational construction grammar approach yields a word-level F1 score of 78.5%, outperforming the CRF approach by 4.5 percentage points.

Keywords: computational construction grammar; Fluid Construction Grammar; FrameNet; semantic frames
Corresponding author: Katrien Beuls, Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium, E-mail:

Funding source: Vlaamse Overheid

Funding source: H2020 Future and Emerging Technologies

Award Identifier / Grant number: 732942

Funding source: Fonds Wetenschappelijk Onderzoek

Award Identifier / Grant number: 75929

Acknowledgment

We would like to thank Luc Steels for his valuable feedback on this work and Remi van Trijp for his work as area editor for Linguistics Vanguard.

  1. Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732942 (funder id: http://dx.doi.org/10.13039/100010664), from the Flemish Government under the ‘Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen’ programme, and from a postdoctoral fellowship of the Research Foundation Flanders (FWO) awarded to PVE (grant No 75929, funder id: http://dx.doi.org/10.13039/501100003130).

References

Baker, Collin, Charles Fillmore & John Lowe. 1998. The Berkeley FrameNet project. In Proceedings of the 17th International Conference on Computational Linguistics volume 1, 86–90. Association for Computational Linguistics.10.3115/980451.980860Search in Google Scholar

Cohn, Trevor & Philip Blunsom. 2005. Semantic role labelling with tree conditional random fields. In Proceedings of the Ninth Conference on Computational Natural Language Learning, 169–172. Association for Computational Linguistics.10.3115/1706543.1706573Search in Google Scholar

Das, Dipanjan, Desai Chen, André Martins, Nathan Schneider & Noah A Smith. 2014. Frame-semantic parsing. Computational Linguistics 40(1). 9–56.10.1162/COLI_a_00163Search in Google Scholar

Dodge, Ellen, Sean Trott, Luca Gilardi & Elise Stickles. 2017. Grammar scaling: Leveraging FrameNet data to increase embodied construction grammar coverage. In 2017 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 27–29, 2017. Palo Alto: AAAI Press.Search in Google Scholar

Dunietz, Jesse, Lori Levin & Jaime Carbonell. 2017. Automatically tagging constructions of causation and their slot-fillers. Transactions of the Association for Computational Linguistics 5. 117–133.10.1162/tacl_a_00050Search in Google Scholar

Ellsworth, Michael & Adam Janin. 2007. Mutaphrase: Paraphrasing with FrameNet. In Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, 143–150. Association for Computational Linguistics.10.3115/1654536.1654566Search in Google Scholar

Fillmore, Charles. 1982. Frame semantics. In The Linguistic Society of Korea (ed.), Linguistics in the morning calm, 111–138. Seoul: Hanshin Publishing Co.10.1016/B0-08-044854-2/00424-7Search in Google Scholar

Fillmore, Charles. 1988. The mechanisms of “construction grammar”. In Annual Meeting of the Berkeley Linguistics Society, vol. 14, 35–55.10.3765/bls.v14i0.1794Search in Google Scholar

Fleischman, Michael, Namhee Kwon & Eduard Hovy. 2003. Maximum entropy models for FrameNet classification. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, 49–56. Association for Computational Linguistics.10.3115/1119355.1119362Search in Google Scholar

Gildea, Daniel & Daniel Jurafsky. 2002. Automatic labeling of semantic roles. Computational Linguistics 28(3). 245–288.10.3115/1075218.1075283Search in Google Scholar

Giuglea, Ana-Maria & Alessandro Moschitti. 2006. Semantic role labeling via FrameNet, VerbNet and PropBank. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, 929–936. Association for Computational Linguistics.10.3115/1220175.1220292Search in Google Scholar

Harabagiu, Sanda, Cosmin Bejan & Morarescu Paul. 2005. Shallow semantics for relation extraction. In IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, 1061–1066.Search in Google Scholar

He, Luheng, Mike Lewis & Luke Zettlemoyer. 2015. Question-answer driven semantic role labeling: Using natural language to annotate natural language. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 643–653.10.18653/v1/D15-1076Search in Google Scholar

Johansson, Richard & Pierre Nugues. 2007. Lth: semantic structure extraction using nonprojective dependency trees. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), 227–230.10.3115/1621474.1621522Search in Google Scholar

Marzinotto, Gabriel, Jérémy Auguste, Frédéric Béchet, Géraldine Damnati & Alexis Nasr. 2018. Semantic frame parsing for information extraction : the CALOR corpus. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 986–993.Search in Google Scholar

McCallum, Andrew & Wei Li. 2003. Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL, vol. 4, 188–191. Association for Computational Linguistics.10.3115/1119176.1119206Search in Google Scholar

Micelli, Vanessa, Remi van Trijp & Joachim De Beule. 2009. Framing Fluid Construction Grammar. In Niels Taatgen & Hedderik van Rijn (eds.), In Proceedings of the 31st Annual Conference of the Cognitive Science Society, 3023–3027. Cognitive Science Society.Search in Google Scholar

Ringgaard, Michael, Rahul Gupta & Fernando CN Pereira. 2017. Sling: A framework for frame semantic parsing. arXiv preprint arXiv:1710.07032.Search in Google Scholar

Shen, Dan & Mirella Lapata. 2007. Using semantic roles to improve question answering. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 12–21. Association for Computational Linguistics.Search in Google Scholar

Shi, Lei & Rada Mihalcea. 2004. An algorithm for open text semantic parsing. In Proceedings of the 3rd Workshop on RObust Methods in Analysis of Natural Language Data, 59–67. Association for Computational Linguistics.10.3115/1621445.1621453Search in Google Scholar

Steels, Luc (ed.). 2011. Design patterns in fluid construction grammar. Amsterdam: John Benjamins.10.1075/cal.11Search in Google Scholar

Thompson, Cynthia, Roger Levy & Christopher Manning. 2003. A generative model for semantic role labeling. In European conference on machine learning, 397–408. Springer.10.1007/978-3-540-39857-8_36Search in Google Scholar

Van Eecke, Paul & Katrien Beuls. 2018. Exploring the creative potential of computational construction grammar. Zeitschrift für Anglistik und Amerikanistik 66(3). 341–355.10.1515/zaa-2018-0029Search in Google Scholar
Received: 2020-02-23
Accepted: 2020-12-21
Published Online: 2021-02-18

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/lingvan-2018-0015
Keywords for this article
computational construction grammar; Fluid Construction Grammar; FrameNet; semantic frames

Articles in the same Issue

  1. Editorial Note
  2. Editorial note
  3. Phonetics & Phonology
  4. Fast Track: fast (nearly) automatic formant-tracking using Praat
  5. Acoustic investigation of anticipatory vowel nasalization in a Caribbean and a non-Caribbean dialect of Spanish
  6. Evidence against a link between learning phonotactics and learning phonological alternations
  7. The extent and degree of utterance-final word lengthening in spontaneous speech from 10 languages
  8. Morphology & Syntax
  9. Brand names as multimodal constructions
  10. NP-internal structure and the distribution of adjectives in Mə̀dʉ́mbὰ
  11. A quantitative investigation of the ellipsis of English relativizers
  12. Positional dependency in Murrinhpatha: expanding the typology of non-canonical morphotactics
  13. Semantics & Pragmatics
  14. Multifactorial Information Management (MIM): summing up the emerging alternative to Information Structure
  15. Language Documentation & Typology
  16. Current trends in grammar writing
  17. Psycholinguistics & Neurolinguistics
  18. Experimental filler design influences error correction rates in a word restoration paradigm
  19. Phonological and morphological roles modulate the perception of consonant variants
  20. Language Acquisition and Language Learning
  21. Sounds like a dynamic system: a unifying approach to Language
  22. Sociolinguistics and Anthropological Linguistics
  23. Using hidden Markov models to find discrete targets in continuous sociophonetic data
  24. “It’s a Whole Vibe”: testing evaluations of grammatical and ungrammatical AAE on Twitter
  25. The sociolinguistics of /l/ in Manchester
  26. Computational & Corpus Linguistics
  27. An empirical study on the contribution of formal and semantic features to the grammatical gender of nouns
  28. A computational construction grammar approach to semantic frame extraction
  29. The “negative end” of change in grammar: terminology, concepts and causes
  30. In order that – a data-driven study of symptoms and causes of obsolescence
  31. Cognitive Linguistics
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  33. Iconicity ratings really do measure iconicity, and they open a new window onto the nature of language
  34. Repetition in Mandarin-speaking children’s dialogs: its distribution and structural dimensions
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