# Computational Semantics and Evaluation Benchmark for Interrogative Sentences via Combinatory Categorial Grammar

arXiv: https://arxiv.org/abs/2312.14737 · HTML: https://mlsanity.com/paper/2312.14737/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 29 references that are in the map.
- First posted on arXiv 22 Dec 2023.

## Builds on (most cited first, 3 of 3)

- [Know What You Don't Know: Unanswerable Questions for SQuAD](https://mlsanity.com/paper/1806.03822/) (2018)
- [A* CCG Parsing with a Supertag and Dependency Factored Model](https://mlsanity.com/paper/1704.06936/) (2017)
- [Towards Universal Semantic Tagging](https://mlsanity.com/paper/1709.10381/) (2017)

## Abstract (arXiv)

We present a compositional semantics for various types of polar questions and wh-questions within the framework of Combinatory Categorial Grammar (CCG). To assess the explanatory power of our proposed analysis, we introduce a question-answering dataset QSEM specifically designed to evaluate the semantics of interrogative sentences. We implement our analysis using existing CCG parsers and conduct evaluations using the dataset. Through the evaluation, we have obtained annotated data with CCG trees and semantic representations for about half of the samples included in QSEM. Furthermore, we discuss the discrepancy between the theoretical capacity of CCG and the capabilities of existing CCG parsers.