Search Results for author: Jingye Li

Found 12 papers, 8 papers with code

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

1 code implementation10 Nov 2022 Bobo Li, Hao Fei, Fei Li, Yuhan Wu, Jinsong Zhang, Shengqiong Wu, Jingye Li, Yijiang Liu, Lizi Liao, Tat-Seng Chua, Donghong Ji

In this work, we introduce a novel task of conversational aspect-based sentiment quadruple analysis, namely DiaASQ, aiming to detect the sentiment quadruple of target-aspect-opinion-sentiment in a dialogue.

Aspect-Based Sentiment Analysis (ABSA) Opinion Mining

TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags

no code implementations1 Nov 2022 Jiang Liu, Donghong Ji, Jingye Li, Dongdong Xie, Chong Teng, Liang Zhao, Fei Li

Concretely, we construct tag representations and embed them into TREM, so that TREM can treat tag and word representations as queries/keys/values and utilize self-attention to model their relationships.

named-entity-recognition Named Entity Recognition +2

Entity-centered Cross-document Relation Extraction

1 code implementation29 Oct 2022 Fengqi Wang, Fei Li, Hao Fei, Jingye Li, Shengqiong Wu, Fangfang Su, Wenxuan Shi, Donghong Ji, Bo Cai

First, we focus on input construction for our RE model and propose an entity-based document-context filter to retain useful information in the given documents by using the bridge entities in the text paths.

Relation Extraction

OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction

1 code implementation COLING 2022 Hu Cao, Jingye Li, Fangfang Su, Fei Li, Hao Fei, Shengqiong Wu, Bobo Li, Liang Zhao, Donghong Ji

Event extraction (EE) is an essential task of information extraction, which aims to extract structured event information from unstructured text.

Event Extraction

Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis

1 code implementation ACL 2022 Wenxuan Shi, Fei Li, Jingye Li, Hao Fei, Donghong Ji

The essential label set consists of the basic labels for this task, which are relatively balanced and applied in the prediction layer.

Dependency Parsing Graph Attention +1

Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extractionwith Rich Syntactic Knowledge

1 code implementation6 May 2021 Shengqiong Wu, Hao Fei, Yafeng Ren, Donghong Ji, Jingye Li

In this paper, we propose to enhance the pair-wise aspect and opinion terms extraction (PAOTE) task by incorporating rich syntactic knowledge.

Boundary Detection POS

Modeling Local Contexts for Joint Dialogue Act Recognition and Sentiment Classification with Bi-channel Dynamic Convolutions

no code implementations COLING 2020 Jingye Li, Hao Fei, Donghong Ji

In this paper, we target improving the joint dialogue act recognition (DAR) and sentiment classification (SC) tasks by fully modeling the local contexts of utterances.

Language Modelling Multi-Task Learning +2

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