Relation Classification
141 papers with code • 8 benchmarks • 23 datasets
Relation Classification is the task of identifying the semantic relation holding between two nominal entities in text.
Source: Structure Regularized Neural Network for Entity Relation Classification for Chinese Literature Text
Benchmarks
These leaderboards are used to track progress in Relation Classification
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TACRED
FewRel
FewRel 2.0
Discovery
GUM
LabPics
Subtasks
Latest papers with no code
Advancing Relation Extraction through Language Probing with Exemplars from Set Co-Expansion
In this paper, we present a multi-faceted approach that integrates representative examples and through co-set expansion.
Improving Zero-shot Relation Classification via Automatically-acquired Entailment Templates
While fully supervised relation classification (RC) models perform well on large-scale datasets, their performance drops drastically in low-resource settings.
A Side-by-side Comparison of Transformers for English Implicit Discourse Relation Classification
Though discourse parsing can help multiple NLP fields, there has been no wide language model search done on implicit discourse relation classification.
Direct Fact Retrieval from Knowledge Graphs without Entity Linking
There has been a surge of interest in utilizing Knowledge Graphs (KGs) for various natural language processing/understanding tasks.
About Evaluation of F1 Score for RECENT Relation Extraction System
This document contains a discussion of the F1 score evaluation used in the article 'Relation Classification with Entity Type Restriction' by Shengfei Lyu, Huanhuan Chen published on Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.
Evaluating BERT-based Scientific Relation Classifiers for Scholarly Knowledge Graph Construction on Digital Library Collections
To address these limitations, we started by creating OCR-noisy texts based on three clean corpora.
KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness
In recent years, Pre-trained Language Models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks.
ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations
This paper aims to quantitatively evaluate the performance of ChatGPT, an interactive large language model, on inter-sentential relations such as temporal relations, causal relations, and discourse relations.
Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph
In this work, we propose Covidia, COVID-19 interdisciplinary academic knowledge graph to bridge the gap between knowledge of COVID-19 on different domains.
End-to-End Models for Chemical-Protein Interaction Extraction: Better Tokenization and Span-Based Pipeline Strategies
End-to-end relation extraction (E2ERE) is an important task in information extraction, more so for biomedicine as scientific literature continues to grow exponentially.
