Papers Relation Classification
“Relation Classification” 태그가 달린 논문 476편 · 필터 해제
Annotation-Inspired Implicit Discourse Relation Classification with Auxiliary Discourse Connective Generation
Implicit discourse relation classification is a challenging task due to the absence of discourse connectives. To overcome this issue, we design an end-to-end neural model to explicitly generate discourse connectives for …
Implicit Discourse Relation ClassificationRelationRelation ClassificationDirect 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. The conventional mechanism to retrieve facts in KGs usually involves three steps: entity…
Entity DisambiguationEntity LinkingKnowledge GraphsLanguage Modelling+3About 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 Comput…
RelationRelation ClassificationRelation ExtractionMatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
We present MatSci-NLP, a natural language benchmark for evaluating the performance of natural language processing (NLP) models on materials science text. We construct the benchmark from publicly available materials scien…
named-entity-recognitionNamed Entity RecognitionQuestion AnsweringRelation ClassificationEvaluating BERT-based Scientific Relation Classifiers for Scholarly Knowledge Graph Construction on Digital Library Collections
The rapid growth of research publications has placed great demands on digital libraries (DL) for advanced information management technologies. To cater to these demands, techniques relying on knowledge-graph structures a…
graph constructionOptical Character RecognitionOptical Character Recognition (OCR)Relation+1KEPLET: 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. On entity-rich textual resources like Wikipedia, Know…
Entity LinkingLanguage ModelingLanguage ModellingRelation+2ChatGPT 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. Given ChatG…
Discourse ParsingIn-Context LearningLanguage ModelingLanguage Modelling+5Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph
The pandemic of COVID-19 has inspired extensive works across different research fields. Existing literature and knowledge platforms on COVID-19 only focus on collecting papers on biology and medicine, neglecting the inte…
ClassificationContrastive LearningManagementRelation ClassificationEnd-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. E2ERE typically involves identifying entities (or n…
Chemical-Protein Interaction Extractionnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+4End-to-End $n$-ary Relation Extraction for Combination Drug Therapies
Combination drug therapies are treatment regimens that involve two or more drugs, administered more commonly for patients with cancer, HIV, malaria, or tuberculosis. Currently there are over 350K articles in PubMed that …
ArticlesDrug–drug Interaction ExtractionRelationRelation Classification+1Borrowing Human Senses: Comment-Aware Self-Training for Social Media Multimodal Classification
Social media is daily creating massive multimedia content with paired image and text, presenting the pressing need to automate the vision and language understanding for various multimodal classification tasks. Compared t…
ClassificationHate Speech DetectionRelation ClassificationSarcasm Detection+2DocRED-FE: A Document-Level Fine-Grained Entity And Relation Extraction Dataset
Joint entity and relation extraction (JERE) is one of the most important tasks in information extraction. However, most existing works focus on sentence-level coarse-grained JERE, which have limitations in real-world sce…
Joint Entity and Relation ExtractionRelationRelation ClassificationRelation Extraction+1LabelPrompt: Effective Prompt-based Learning for Relation Classification
Recently, prompt-based learning has gained popularity across many natural language processing (NLP) tasks by reformulating them into a cloze-style format to better align pre-trained language models (PLMs) with downstream…
ClassificationContrastive LearningLanguage ModellingRelation+1A Marker-based Neural Network System for Extracting Social Determinants of Health
Objective. The impact of social determinants of health (SDoH) on patients' healthcare quality and the disparity is well-known. Many SDoH items are not coded in structured forms in electronic health records. These items a…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3RankDNN: Learning to Rank for Few-shot Learning
This paper introduces a new few-shot learning pipeline that casts relevance ranking for image retrieval as binary ranking relation classification. In comparison to image classification, ranking relation classification is…
Few-Shot Learningimage-classificationImage ClassificationImage Retrieval+4CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification
Recently, prefix-tuning was proposed to efficiently adapt pre-trained language models to a broad spectrum of natural language classification tasks. It leverages soft prefix as task-specific indicators and language verbal…
ClassificationcounterfactualEntity TypingMachine Translation+6Multilingual Relation Classification via Efficient and Effective Prompting
Prompting pre-trained language models has achieved impressive performance on various NLP tasks, especially in low data regimes. Despite the success of prompting in monolingual settings, applying prompt-based methods in m…
ClassificationRelationRelation ClassificationGenerative Prompt Tuning for Relation Classification
Using prompts to explore the knowledge contained within pre-trained language models for downstream tasks has now become an active topic. Current prompt tuning methods mostly convert the downstream tasks to masked languag…
ClassificationLanguage ModelingLanguage ModellingMasked Language Modeling+4PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text
Scientific action graphs extraction from materials synthesis procedures is important for reproducible research, machine automation, and material prediction. But the lack of annotated data has hindered progress in this fi…
ArticlesNamed Entity RecognitionNamed Entity Recognition (NER)Relation Classification+2Pre-trained Sentence Embeddings for Implicit Discourse Relation Classification
Implicit discourse relations bind smaller linguistic units into coherent texts. Automatic sense prediction for implicit relations is hard, because it requires understanding the semantics of the linked arguments. Furtherm…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsRelation+3