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Dialog Relation Extraction

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.

Papers

Showing 114 of 14 papers

TitleStatusHype
GRASP: Guiding model with RelAtional Semantics using Prompt for Dialogue Relation ExtractionCode1
Global inference with explicit syntactic and discourse structures for dialogue-level relation extractionCode0
Document-Level Relation Extraction with Sentences Importance Estimation and FocusingCode1
Speaker-Oriented Latent Structures for Dialogue-Based Relation ExtractionCode0
D-REX: Dialogue Relation Extraction with ExplanationsCode0
Graph Based Network with Contextualized Representations of Turns in DialogueCode1
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues0
Semantic Representation for Dialogue ModelingCode1
KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation ExtractionCode1
An Embarrassingly Simple Model for Dialogue Relation ExtractionCode0
GDPNet: Refining Latent Multi-View Graph for Relation ExtractionCode1
DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic DialoguesCode1
Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention NetworksCode1
Dialogue-Based Relation ExtractionCode1
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