# DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis

Source: [DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis](<https://www.sota2.com/research/paper/68fa6f721e209131cea45a40>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-04T03:43:32.551Z

Authors: Bobo Li, Hao Fei, Fei Li, Yuhan Wu, Jinsong Zhang, Shengqiong Wu, Jingye Li, Yijiang Liu, Lizi Liao, Tat-Seng Chua, Donghong Ji

Published: 2022-11-10T17:18:20.000Z

## Abstract

The rapid development of aspect-based sentiment analysis (ABSA) within recent decades shows great potential for real-world society. The current ABSA works, however, are mostly limited to the scenario of a single text piece, leaving the study in dialogue contexts unexplored. To bridge the gap between fine-grained sentiment analysis and conversational opinion mining, in this work, we introduce a novel task of conversational aspect-based sentiment quadruple analysis, namely DiaASQ, aiming to detect the quadruple of target-aspect-opinion-sentiment in a dialogue. We manually construct a large-scale high-quality DiaASQ dataset in both Chinese and English languages. We deliberately develop a neural model to benchmark the task, which advances in effectively performing end-to-end quadruple prediction, and manages to incorporate rich dialogue-specific and discourse feature representations for better cross-utterance quadruple extraction. We hope the new benchmark will spur more advancements in the sentiment analysis community.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Dialogue Aspect-based Sentiment Quadruple Extraction on DiaASQ ZH (test)](<https://www.sota2.com/research/sota/dialogue-aspect-based-sentiment-quadruple-extraction-on-diaasq-zh-test.md>): Dialogue Aspect-based Sentiment Quadruple Extraction; DiaASQ ZH (Chinese) (test); Pair Extraction F1 (Target-Aspect): 48.61.

- [Dialogue Aspect-based Sentiment Quadruple Extraction on DiaASQ EN (test)](<https://www.sota2.com/research/sota/dialogue-aspect-based-sentiment-quadruple-extraction-on-diaasq-en-test.md>): Dialogue Aspect-based Sentiment Quadruple Extraction; DiaASQ EN (test); Pair F1 (Target-Aspect): 0.4791.

- [Aspect-based Sentiment Quadruple Extraction on LASQ Uzbek](<https://www.sota2.com/research/sota/aspect-based-sentiment-quadruple-extraction-on-lasq-uzbek.md>): Aspect-based Sentiment Quadruple Extraction; LASQ Uzbek; Entity Target F1: 75.62.

- [Aspect-based Sentiment Quadruple Extraction on LASQ Uyghur](<https://www.sota2.com/research/sota/aspect-based-sentiment-quadruple-extraction-on-lasq-uyghur.md>): Aspect-based Sentiment Quadruple Extraction; LASQ Uyghur; Entity Target F1: 79.74.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2211.05705>)

[PDF](<https://arxiv.org/pdf/2211.05705.pdf>)

[Implementation](<https://github.com/unikcc/DiaASQ>)