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Fluid Construction Grammar: State of the Art and Future Outlook

Summary

The paper is a survey. It summarizes the Fluid Construction Grammar (FCG) research program. FCG is a computational framework that formalizes the tenets of construction grammar and has its own engine for comprehending and producing utterances on the basis of constructions. The authors situate FCG alongside other computational approaches, ECG and SBCG. They explain why construction grammar needs formalization: to test the internal consistency of theories, to evaluate them on corpora, to have a shared standard for exchange among researchers, and to build language technologies. They then show how FCG implements four basic tenets. A construction is a form-meaning pairing with separate preconditions for each direction of processing. Processing itself is framed as a search through a state space with unification over a transient feature structure. The paper also describes how constructions are learned by generalizing over recurring syntactico-semantic patterns and gives examples of applications. The authors conclude that a mature framework already exists and that the automatic learning of large usage-based grammars suitable for both comprehension and production has become feasible. For NLP, this is a path toward interpretable bidirectional language processing grounded in linguistic theory.

Key points

  • Form and meaning in FCG are defined in terms of communication. Form is everything the speaker externalizes and the listener perceives. Meaning is what the speaker intends to convey and the listener reconstructs. This division replaces the traditional levels of analysis.
  • A construction has two parts: preconditions (separately for comprehension and production) and the contribution it adds. Application proceeds in two steps. First, the preconditions are matched against the transient structure via subset unification; then the postconditions are merged into it. Lexical and grammatical constructions are described by a single data structure, and there are no obligatory features.
  • Applications include experiments with emergent languages, demos of visual question answering and visual dialog, and two tools for analyzing climate debates that detect causal frames: Penelope Climate Change Opinion Observatory and Penelope Opinion Facilitator. Another tool is CCxG Explorer. It searches a corpus for examples by semantic structure, independently of morphosyntactic expression.
  • Four challenges for the future are identified:
    • scaling up the modeling of systemic relations among hundreds of thousands of constructions;
    • improving the learning operators, in particular for agreement, semantic generalizations, and working with the speech signal instead of strings;
    • turning large learned grammars into practical applications;
    • creating accessible tooling for AI/NLP engineers.
  • Resource: fcg-net.org. The work was funded by FWO and Horizon 2020 (MUHAI project, grant agreement No. 951846).

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cite

Cite as Katrien Beuls and Paul Van Eecke. 2023. Fluid Construction Grammar: State of the Art and Future Outlook. Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023).

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{beuls2023fluid,
  title = {{Fluid Construction Grammar: State of the Art and Future Outlook}},
  author = {Katrien Beuls and Paul {Van Eecke}},
  booktitle = {Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)},
  year = {2023},
  url = {https://aclanthology.org/2023.cxgsnlp-1.6/}
}

References

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