https://github.com/JiaQiSJTU/DialogueRelationClassification
공식 코드DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues
Papers with Code 아카이브
Dialog Relation Extraction
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Dialog Relation Extraction is the task of predicting the relation type between entities mentioned in dialogue. It uses multiple tokens to capture possible relations between pairs of entities in the dialogue. The popular benchmark for this task is the DialogRE dataset. The models are typically evaluated with the metric of F1 Score for both standard-setting and conversational settings.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/XueFuzhao/GDPNet
공식 코드GDPNet: Refining Latent Multi-View Graph for Relation Extraction
https://github.com/alon-albalak/D-REX
공식 코드https://github.com/blacknoodle/tucore-gcn
공식 코드Graph Based Network with Contextualized Representations of Turns in Dialogue
https://github.com/declare-lab/dialog-HGAT
공식 코드Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks
https://github.com/frankdarkluo/sols
공식 코드Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction
https://github.com/muyeby/AMR-Dialogue
공식 코드https://github.com/rgop13/GRASP
공식 코드GRASP: Guiding model with RelAtional Semantics using Prompt for Dialogue Relation Extraction
https://github.com/shawx825/hidialog
공식 코드Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention
https://github.com/xwjim/sief
공식 코드Document-Level Relation Extraction with Sentences Importance Estimation and Focusing
https://github.com/zjunlp/KnowPrompt
공식 코드KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction
https://github.com/XueFuzhao/SimpleRE
An Embarrassingly Simple Model for Dialogue Relation Extraction
https://github.com/nlpdata/dialogre
https://github.com/scofield7419/DiaRE-D2G
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.