A computational construction grammar approach to semantic frame extraction
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Katrien Beuls
,
Paul Van Eecke
und
Vanja Sophie Cangalovic
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.
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.
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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.10.3115/980451.980860Suche 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.10.3115/1706543.1706573Suche 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_00163Suche 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.Suche 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_00050Suche 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.10.3115/1654536.1654566Suche 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/B0-08-044854-2/00424-7Suche 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.v14i0.1794Suche 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.10.3115/1119355.1119362Suche in Google Scholar
Gildea, Daniel & Daniel Jurafsky. 2002. Automatic labeling of semantic roles. Computational Linguistics 28(3). 245–288.10.3115/1075218.1075283Suche 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.10.3115/1220175.1220292Suche 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.Suche 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/D15-1076Suche 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), 227–230.10.3115/1621474.1621522Suche 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.Suche 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.10.3115/1119176.1119206Suche 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.Suche in Google Scholar
Ringgaard, Michael, Rahul Gupta & Fernando CN Pereira. 2017. Sling: A framework for frame semantic parsing. arXiv preprint arXiv:1710.07032.Suche 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.Suche 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.10.3115/1621445.1621453Suche in Google Scholar
Steels, Luc (ed.). 2011. Design patterns in fluid construction grammar. Amsterdam: John Benjamins.10.1075/cal.11Suche 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_36Suche 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-2018-0029Suche in Google Scholar
© 2021 Walter de Gruyter GmbH, Berlin/Boston
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- Editorial Note
- Editorial note
- Phonetics & Phonology
- Fast Track: fast (nearly) automatic formant-tracking using Praat
- Acoustic investigation of anticipatory vowel nasalization in a Caribbean and a non-Caribbean dialect of Spanish
- Evidence against a link between learning phonotactics and learning phonological alternations
- The extent and degree of utterance-final word lengthening in spontaneous speech from 10 languages
- Morphology & Syntax
- Brand names as multimodal constructions
- NP-internal structure and the distribution of adjectives in Mə̀dʉ́mbὰ
- A quantitative investigation of the ellipsis of English relativizers
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- Semantics & Pragmatics
- Multifactorial Information Management (MIM): summing up the emerging alternative to Information Structure
- Language Documentation & Typology
- Current trends in grammar writing
- Psycholinguistics & Neurolinguistics
- Experimental filler design influences error correction rates in a word restoration paradigm
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- Language Acquisition and Language Learning
- Sounds like a dynamic system: a unifying approach to Language
- Sociolinguistics and Anthropological Linguistics
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