# GCRE-GPT: A Generative Model for Comparative Relation Extraction

arXiv: https://arxiv.org/abs/2303.08601 · HTML: https://mlsanity.com/paper/2303.08601/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 14 references that are in the map.
- First posted on arXiv 15 Mar 2023.

## Builds on (most cited first, 5 of 5)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://mlsanity.com/paper/1911.00536/) (2019)
- [Modeling Coverage for Neural Machine Translation](https://mlsanity.com/paper/1601.04811/) (2016)
- [MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation](https://mlsanity.com/paper/2203.13560/) (2022)
- [Neural Machine Translation with Explicit Phrase Alignment](https://mlsanity.com/paper/1911.11520/) (2019)

## Built on by (most cited first, 2 of 2)

- [CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language Model](https://mlsanity.com/paper/2404.18085/) (2024)
- ["This Suits You the Best": Query Focused Comparative Explainable Summarization](https://mlsanity.com/paper/2507.04733/) (2025)

## Abstract (arXiv)

Given comparative text, comparative relation extraction aims to extract two targets (eg two cameras) in comparison and the aspect they are compared for (eg image quality). The extracted comparative relations form the basis of further opinion analysis.Existing solutions formulate this task as a sequence labeling task, to extract targets and aspects. However, they cannot directly extract comparative relation(s) from text. In this paper, we show that comparative relations can be directly extracted with high accuracy, by generative model. Based on GPT-2, we propose a Generation-based Comparative Relation Extractor (GCRE-GPT). Experiment results show that modelname achieves state-of-the-art accuracy on two datasets.