Papers Relation Classification
“Relation Classification” 태그가 달린 논문 476편 · 필터 해제
CrossRE: A Cross-Domain Dataset for Relation Extraction
Relation Extraction (RE) has attracted increasing attention, but current RE evaluation is limited to in-domain evaluation setups. Little is known on how well a RE system fares in challenging, but realistic out-of-distrib…
RelationRelation ClassificationRelation ExtractionImproving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning
“Event Temporal Relation Classification (ETRC) is crucial to natural language understanding. In recent years, the mainstream ETRC methods may not take advantage of lots of semantic information contained in golden tempora…
Contrastive LearningData AugmentationLanguage ModelingLanguage Modelling+4Logical Form Generation via Multi-task Learning for Complex Question Answering over Knowledge Bases
Question answering over knowledge bases (KBQA) for complex questions is a challenging task in natural language processing. Recently, generation-based methods that translate natural language questions to executable logica…
Entity DisambiguationFormMulti-Task LearningQuestion Answering+2Dependency-aware Prototype Learning for Few-shot Relation Classification
Few-shot relation classification aims to classify the relation type between two given entities in a sentence by training with a few labeled instances for each relation. However, most of existing models fail to distinguis…
ClassificationFew-Shot Relation ClassificationRelationRelation Classification+1Enhancing Contextual Word Representations Using Embedding of Neighboring Entities in Knowledge Graphs
Pre-trained language models (PLMs) such as BERT and RoBERTa have dramatically improved the performance of various natural language processing tasks. Although these models are trained on large amounts of raw text, they ha…
Entity TypingKnowledge GraphsRelationRelation ClassificationHow about Time? Probing a Multilingual Language Model for Temporal Relations
This paper presents a comprehensive set of probing experiments using a multilingual language model, XLM-R, for temporal relation classification between events in four languages. Results show an advantage of contextualize…
Language ModelingLanguage ModellingRelationRelation Classification+3Multi-Perspective Document Revision
This paper presents a novel multi-perspective document revision task. In conventional studies on document revision, tasks such as grammatical error correction, sentence reordering, and discourse relation classification h…
Grammatical Error CorrectionRelation ClassificationSentenceLabel distributions help implicit discourse relation classification
Implicit discourse relations can convey more than one relation sense, but much of the research on discourse relations has focused on single relation senses. Recently, DiscoGeM, a novel multi-domain corpus, which contains…
ClassificationImplicit Discourse Relation ClassificationRelationRelation ClassificationZero-shot Event Causality Identification with Question Answering
Extraction of event causality and especially implicit causality from text data is a challenging task. Causality is often treated as a specific relation type and can be considered as a part of relation extraction or relat…
ArticlesEvent Causality IdentificationMultiple-choicePassage Retrieval+8AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification
In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the problem of drug–target …
Drug DiscoveryRelation ClassificationSentenceSentence ClassificationViRel: Unsupervised Visual Relations Discovery with Graph-level Analogy
Visual relations form the basis of understanding our compositional world, as relationships between visual objects capture key information in a scene. It is then advantageous to learn relations automatically from the data…
RelationRelation ClassificationOPI at SemEval-2022 Task 10: Transformer-based Sequence Tagging with Relation Classification for Structured Sentiment Analysis
This paper presents our solution for SemEval-2022 Task 10: Structured Sentiment Analysis. The solution consisted of two modules: the first for sequence tagging and the second for relation classification. In both modules …
Relation ClassificationSentiment AnalysisImproving Few-Shot Relation Classification by Prototypical Representation Learning with Definition Text
Few-shot relation classification is difficult because the few instances available may not represent well the relation patterns. Some existing approaches explored extra information such as relation definition, in addition…
Few-Shot Relation ClassificationRelationRelation ClassificationRepresentation LearningRCL: Relation Contrastive Learning for Zero-Shot Relation Extraction
Zero-shot relation extraction aims to identify novel relations which cannot be observed at the training stage. However, it still faces some challenges since the unseen relations of instances are similar or the input sent…
Contrastive LearningData AugmentationRelationRelation Classification+1Enhancing Targeted Minority Class Prediction in Sentence-Level Relation Extraction
Sentence-level relation extraction (RE) has a highly imbalanced data distribution that about 80% of data are labeled as negative, i.e., no relation; and there exist minority classes (MC) among positive labels; furthermor…
RelationRelation ClassificationRelation ExtractionSentenceDiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations
We present DiscoGeM, a crowdsourced corpus of 6,505 implicit discourse relations from three genres: political speech, literature, and encyclopedic texts. Each instance was annotated by 10 crowd workers. Various label agg…
RelationRelation ClassificationDeepREF: A Framework for Optimized Deep Learning-based Relation Classification
The Relation Extraction (RE) is an important basic Natural Language Processing (NLP) for many applications, such as search engines, recommender systems, question-answering systems and others. There are many studies in th…
Deep LearningQuestion AnsweringRecommendation SystemsRelation+2Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction
Compared with traditional sentence-level relation extraction, document-level relation extraction is a more challenging task where an entity in a document may be mentioned multiple times and associated with multiple relat…
Document-level Relation ExtractionRelationRelation ClassificationRelation Extraction+1Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding
Prompt Tuning has been largely successful as a parameter-efficient method of conditioning large-scale pre-trained language models to perform downstream tasks. Thus far, soft prompt tuning learns a fixed set of task-speci…
Natural Language UnderstandingNERQuantizationRelation Classification+1DeepStruct: Pretraining of Language Models for Structure Prediction
We introduce a method for improving the structural understanding abilities of language models. Unlike previous approaches that finetune the models with task-specific augmentation, we pretrain language models on a collect…
coreference-resolutionCoreference ResolutionDialogue State TrackingEvent Extraction+14