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Found 17 papers, 7 papers with code
Pre-training Entity Relation Encoder with Intra-span and Inter-span Information
In particular, a span encoder is trained to recover a random shuffling of tokens in a span, and a span pair encoder is trained to predict positive pairs that are from the same sentences and negative pairs that are from different sentences using contrastive loss.
ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base
Analogical reasoning is a fundamental cognitive ability of humans.
HIORE: Leveraging High-order Interactions for Unified Entity Relation Extraction
Entity relation extraction consists of two sub-tasks: entity recognition and relation extraction.
Converge to the Truth: Factual Error Correction via Iterative Constrained Editing
Given a possibly false claim sentence, how can we automatically correct it with minimal editing?
Few Clean Instances Help Denoising Distant Supervision
Existing distantly supervised relation extractors usually rely on noisy data for both model training and evaluation, which may lead to garbage-in-garbage-out systems.
Causal Intervention Improves Implicit Sentiment Analysis
In this work, we propose a causal intervention model for Implicit Sentiment Analysis using Instrumental Variable (ISAIV).
E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning
Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-of-its-kind Explainable Knowledge-intensive Analogical Reasoning benchmark (E-KAR).
Learning Logic Rules for Document-level Relation Extraction
LogiRE treats logic rules as latent variables and consists of two modules: a rule generator and a relation extractor.
Ranked #20 on
Relation Extraction
on DocRED
NAIL: A Challenging Benchmark for Na\"ive Logical Reasoning
Logical reasoning over natural text is an important capability towards human level intelligence.
UniRE: A Unified Label Space for Entity Relation Extraction
Entities and relations are represented by squares and rectangles in the table.
Probabilistic Graph Reasoning for Natural Proof Generation
In this paper, we propose PRobr, a novel approach for joint answer prediction and proof generation.
ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction
Current state-of-the-art systems for joint entity relation extraction (Luan et al., 2019; Wad-den et al., 2019) usually adopt the multi-task learning framework.
Is ``hot pizza'' Positive or Negative? Mining Target-aware Sentiment Lexicons
Modelling a word{'}s polarity in different contexts is a key task in sentiment analysis.
LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification
The final claim verification is based on all latent variables.
Joint Type Inference on Entities and Relations via Graph Convolutional Networks
We develop a new paradigm for the task of joint entity relation extraction.
Ranked #1 on
Relation Extraction
on ACE 2005
(Sentence Encoder metric)
Extracting Entities and Relations with Joint Minimum Risk Training
We investigate the task of joint entity relation extraction.
Ranked #1 on
Relation Extraction
on ACE 2005
(Sentence Encoder metric)
Large-scale Opinion Relation Extraction with Distantly Supervised Neural Network
We investigate the task of open domain opinion relation extraction.
