The Computational Learning of Construction Grammars: State of the Art and Prospective Roadmap

Autor:	Doumen, Jonas, Schmalz, Veronica Juliana, Beuls, Katrien, Van Eecke, Paul
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	This paper documents and reviews the state of the art concerning computational models of construction grammar learning. It brings together prior work on the computational learning of form-meaning pairings, which has so far been studied in several distinct areas of research. The goal of this paper is threefold. First of all, it aims to synthesise the variety of methodologies that have been proposed to date and the results that have been obtained. Second, it aims to identify those parts of the challenge that have been successfully tackled and reveal those that require further research. Finally, it aims to provide a roadmap which can help to boost and streamline future research efforts on the computational learning of large-scale, usage-based construction grammars. Comment: Peer-reviewed author's draft of a journal article to appear in Constructions and Frames (2025)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.07606 Zobrazit plný text záznamu View this record from Arxiv