Papers Relation Classification
“Relation Classification” 태그가 달린 논문 476편 · 필터 해제
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation
We cast a suite of information extraction tasks into a text-to-triple translation framework. Instead of solving each task relying on task-specific datasets and models, we formalize the task as a translation between task-…
Factual probeLanguage ModelingLanguage ModellingOpen Information Extraction+2Distilling Relation Embeddings from Pre-trained Language Models
Pre-trained language models have been found to capture a surprisingly rich amount of lexical knowledge, ranging from commonsense properties of everyday concepts to detailed factual knowledge about named entities. Among o…
Knowledge GraphsLanguage ModelingLanguage ModellingRelation+1DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection
This paper describes our submission to the DISRPT2021 Shared Task on Discourse Unit Segmentation, Connective Detection, and Relation Classification. Our system, called DisCoDisCo, is a Transformer-based neural classifier…
ClassificationConnective DetectionDiscourse ParsingDiscourse Segmentation+5Supervised Relation Classification as Two-way Span-Prediction
Most of the current supervised relation classification (RC) algorithms use a single embedding to represent the relation between a pair of entities. We argue that a better approach is to treat the RC task as a Span-Predic…
ClassificationPredictionQuestion AnsweringRelation+2SORNet: Spatial Object-Centric Representations for Sequential Manipulation
Sequential manipulation tasks require a robot to perceive the state of an environment and plan a sequence of actions leading to a desired goal state. In such tasks, the ability to reason about spatial relations among obj…
ObjectRelation ClassificationRepresentation LearningSpatial Reasoning+1Does Knowledge Help General NLU? An Empirical Study
It is often observed in knowledge-centric tasks (e.g., common sense question and answering, relation classification) that the integration of external knowledge such as entity representation into language models can help …
Common Sense ReasoningLanguage ModelingLanguage ModellingNatural Language Understanding+1Active Learning for Interactive Relation Extraction in a French Newspaper’s Articles
Relation extraction is a subtask of natural langage processing that has seen many improvements in recent years, with the advent of complex pre-trained architectures. Many of these state-of-the-art approaches are tested a…
Active LearningArticlesRelationRelation Classification+2TIMERS: Document-level Temporal Relation Extraction
We present TIMERS - a TIME, Rhetorical and Syntactic-aware model for document-level temporal relation classification in the English language. Our proposed method leverages rhetorical discourse features and temporal argum…
RelationRelation ClassificationRelation ExtractionTemporal Relation Classification+1Entity Enhancement for Implicit Discourse Relation Classification in the Biomedical Domain
Implicit discourse relation classification is a challenging task, in particular when the text domain is different from the standard Penn Discourse Treebank (PDTB; Prasad et al., 2008) training corpus domain (Wall Street …
Implicit Discourse Relation ClassificationRelationRelation ClassificationVerb Metaphor Detection via Contextual Relation Learning
Correct natural language understanding requires computers to distinguish the literal and metaphorical senses of a word. Recent neu- ral models achieve progress on verb metaphor detection by viewing it as sequence labelin…
Natural Language UnderstandingRelationRelation ClassificationDependency-driven Relation Extraction with Attentive Graph Convolutional Networks
Syntactic information, especially dependency trees, has been widely used by existing studies to improve relation extraction with better semantic guidance for analyzing the context information associated with the given en…
RelationRelation ClassificationRelation ExtractionFrom Learning-to-Match to Learning-to-Discriminate:Global Prototype Learning for Few-shot Relation Classification
“Few-shot relation classification has attracted great attention recently and is regarded as an ef-fective way to tackle the long-tail problem in relation classification. Most previous works onfew-shot relation classifica…
ClassificationFew-Shot Relation ClassificationRelationRelation ClassificationNS-Hunter: BERT-Cloze Based Semantic Denoising for Distantly Supervised Relation Classification
“Distant supervision can generate large-scale relation classification data quickly and economi-cally. However a great number of noise sentences are introduced which can not express their labeled relations. By means of pr…
ClassificationDenoisingLanguage ModellingRelation+2Let’s be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
In implicit discourse relation classification, we want to predict the relation between adjacent sentences in the absence of any overt discourse connectives. This is challenging even for humans, leading to shortage of ann…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsLanguage Modeling+4UniRE: A Unified Label Space for Entity Relation Extraction
Many joint entity relation extraction models setup two separated label spaces for the two sub-tasks (i.e., entity detection and relation classification). We argue that this setting may hinder the information interaction …
DecoderRelationRelation ClassificationRelation Extraction+1From Argument Search to Argumentative Dialogue: A Topic-independent Approach to Argument Acquisition for Dialogue Systems
Despite the remarkable progress in the field of computational argumentation, dialogue systems concerned with argumentative tasks often rely on structured knowledge about arguments and their relations. Since the manual ac…
Relation ClassificationA Span-Based Model for Joint Overlapped and Discontinuous Named Entity Recognition
Research on overlapped and discontinuous named entity recognition (NER) has received increasing attention. The majority of previous work focuses on either overlapped or discontinuous entities. In this paper, we propose a…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3One-shot to Weakly-Supervised Relation Classification using Language Models
Relation classification aims at detecting a particular relation type between two entities in text, whose methods mostly requires annotated data. Data annotation is either a manual process for supervised learning, or auto…
RelationRelation ClassificationEnhancing Question Generation with Commonsense Knowledge
Question generation (QG) is to generate natural and grammatical questions that can be answered by a specific answer for a given context. Previous sequence-to-sequence models suffer from a problem that asking high-quality…
Multi-Task LearningQuestion GenerationQuestion-GenerationRelation ClassificationLet's be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
In implicit discourse relation classification, we want to predict the relation between adjacent sentences in the absence of any overt discourse connectives. This is challenging even for humans, leading to shortage of ann…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsLanguage Modeling+4