# Proposition from the Perspective of Chinese Language: A Chinese Proposition Classification Evaluation Benchmark

arXiv: https://arxiv.org/abs/2309.09602 · HTML: https://mlsanity.com/paper/2309.09602/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 28 references that are in the map.
- First posted on arXiv 18 Sep 2023.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Emergent Abilities of Large Language Models](https://mlsanity.com/paper/2206.07682/) (2022)
- [BLOOM: A 176B-Parameter Open-Access Multilingual Language Model](https://mlsanity.com/paper/2211.05100/) (2022)
- [Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning](https://mlsanity.com/paper/2010.15875/) (2020)
- [Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text](https://mlsanity.com/paper/2105.03659/) (2021)
- [DAGN: Discourse-Aware Graph Network for Logical Reasoning](https://mlsanity.com/paper/2103.14349/) (2021)
- [MERIt: Meta-Path Guided Contrastive Learning for Logical Reasoning](https://mlsanity.com/paper/2203.00357/) (2022)
- [The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing](https://mlsanity.com/paper/2106.08037/) (2021)

## Abstract (arXiv)

Existing propositions often rely on logical constants for classification. Compared with Western languages that lean towards hypotaxis such as English, Chinese often relies on semantic or logical understanding rather than logical connectives in daily expressions, exhibiting the characteristics of parataxis. However, existing research has rarely paid attention to this issue. And accurately classifying these propositions is crucial for natural language understanding and reasoning. In this paper, we put forward the concepts of explicit and implicit propositions and propose a comprehensive multi-level proposition classification system based on linguistics and logic. Correspondingly, we create a large-scale Chinese proposition dataset PEACE from multiple domains, covering all categories related to propositions. To evaluate the Chinese proposition classification ability of existing models and explore their limitations, We conduct evaluations on PEACE using several different methods including the Rule-based method, SVM, BERT, RoBERTA, and ChatGPT. Results show the importance of properly modeling the semantic features of propositions. BERT has relatively good proposition classification capability, but lacks cross-domain transferability. ChatGPT performs poorly, but its classification ability can be improved by providing more proposition information. Many issues are still far from being resolved and require further study.