LLMs show measurable deficiencies in both decomposition and composition during natural-to-formal conversion, with decomposition errors dominating, under the new DEDC evaluation framework.
A Survey of Syntactic-Semantic Parsing Based on Constituent and Dependency Structures
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abstract
Syntactic and semantic parsing has been investigated for decades, which is one primary topic in the natural language processing community. This article aims for a brief survey on this topic. The parsing community includes many tasks, which are difficult to be covered fully. Here we focus on two of the most popular formalizations of parsing: constituent parsing and dependency parsing. Constituent parsing is majorly targeted to syntactic analysis, and dependency parsing can handle both syntactic and semantic analysis. This article briefly reviews the representative models of constituent parsing and dependency parsing, and also dependency graph parsing with rich semantics. Besides, we also review the closely-related topics such as cross-domain, cross-lingual and joint parsing models, parser application as well as corpus development of parsing in the article.
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cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Investigating the (De)Composition Capabilities of Large Language Models in Natural-to-Formal Language Conversion
LLMs show measurable deficiencies in both decomposition and composition during natural-to-formal conversion, with decomposition errors dominating, under the new DEDC evaluation framework.