Exploring the Constructicon: Linguistic Analysis of a Computational CxG
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Abstract (arXiv)
Recent work has formulated the task for computational construction grammar as producing a constructicon given a corpus of usage. Previous work has evaluated these unsupervised grammars using both internal metrics (for example, Minimum Description Length) and external metrics (for example, performance on a dialectology task). This paper instead takes a linguistic approach to evaluation, first learning a constructicon and then analyzing its contents from a linguistic perspective. This analysis shows that a learned constructicon can be divided into nine major types of constructions, of which Verbal and Nominal are the most common. The paper also shows that both the token and type frequency of constructions can be used to model variation across registers and dialects.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 30 Jan 2023.
Builds on
14 of 33 references.
References · 14
- 2015Character-level Convolutional Networks for Text Classificationcited by 2,293
- 2019Compressive Transformers for Long-Range Sequence Modellingcited by 699
- 2018Learning Word Vectors for 157 Languagescited by 279
- 2020Mapping Languages: The Corpus of Global Language Usecited by 42
- 2019Modeling Global Syntactic Variation in English Using Dialect Classificationcited by 13
- 2019Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammarcited by 11
- 2021Finding Variants for Construction-Based Dialectometry: A Corpus-Based Approach to Regional CxGscited by 11
- 2021Global Syntactic Variation in Seven Languages: Towards a Computational Dialectologycited by 11
- 2014A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Taggingcited by 9
- 2019Modeling the Complexity and Descriptive Adequacy of Construction Grammarscited by 9
- 2021Production vs Perception: The Role of Individuality in Usage-Based Grammar Inductioncited by 6
- 2021Learned Construction Grammars Converge Across Registers Given Increased Exposurecited by 6
Built on by
Citing papers per year: 2023: 2; 2024: 1.
3 papers.
- 2023Enhancing Language Representation with Constructional Information for Natural Language Understandingcited by 2
- 2023Syntactic Variation Across the Grammar: Modelling a Complex Adaptive Systemcited by 1
- 2024The Computational Learning of Construction Grammars: State of the Art and Prospective Roadmapcited by 1
- 2024The Computational Learning of Construction Grammars: State of the Art and Prospective Roadmap10 Jul 2024
- 2023Syntactic Variation Across the Grammar: Modelling a Complex Adaptive System21 Sep 2023
- 2023Enhancing Language Representation with Constructional Information for Natural Language Understanding5 Jun 2023