Papers Knowledge Base Population
“Knowledge Base Population” 태그가 달린 논문 140편 · 필터 해제
Autoregressive Language Models for Knowledge Base Population: A case study in the space mission domain
Knowledge base population KBP plays a crucial role in populating and maintaining knowledge bases up-to-date in organizations by leveraging domain corpora. Motivated by the increasingly large context windows supported by …
Knowledge Base PopulationLanguage ModelingLanguage ModellingTextual Entailment for Effective Triple Validation in Object Prediction
Knowledge base population seeks to expand knowledge graphs with facts that are typically extracted from a text corpus. Recently, language models pretrained on large corpora have been shown to contain factual knowledge th…
Knowledge Base PopulationKnowledge GraphsLanguage ModelingLanguage Modelling+4Expanding the Vocabulary of BERT for Knowledge Base Construction
Knowledge base construction entails acquiring structured information to create a knowledge base of factual and relational data, facilitating question answering, information retrieval, and semantic understanding. The chal…
Knowledge Base ConstructionKnowledge Base PopulationLanguage ModelingLanguage Modelling+3CKBP v2: Better Annotation and Reasoning for Commonsense Knowledge Base Population
Commonsense Knowledge Bases (CSKB) Population, which aims at automatically expanding knowledge in CSKBs with external resources, is an important yet hard task in NLP. Fang et al. (2021a) proposed a CSKB Population (CKBP)…
Knowledge Base PopulationQuestion AnsweringPseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population
Commonsense Knowledge Base (CSKB) Population aims at reasoning over unseen entities and assertions on CSKBs, and is an important yet hard commonsense reasoning task. One challenge is that it requires out-of-domain genera…
Domain GeneralizationKnowledge Base PopulationEA^2E: Improving Consistency with Event Awareness for Document-Level Argument Extraction
Events are inter-related in documents. Motivated by the one-sense-per-discourse theory, we hypothesize that a participant tends to play consistent roles across multiple events in the same document. However recent work on…
Event Argument ExtractionKnowledge Base PopulationQuestion AnsweringSTable: Table Generation Framework for Encoder-Decoder Models
The output structure of database-like tables, consisting of values structured in horizontal rows and vertical columns identifiable by name, can cover a wide range of NLP tasks. Following this constatation, we propose a f…
DecoderJoint Entity and Relation ExtractionKnowledge Base PopulationRelation ExtractionEA$^2$E: Improving Consistency with Event Awareness for Document-Level Argument Extraction
Events are inter-related in documents. Motivated by the one-sense-per-discourse theory, we hypothesize that a participant tends to play consistent roles across multiple events in the same document. However recent work on…
Event Argument ExtractionKnowledge Base PopulationQuestion AnsweringBEEDS: Large-Scale Biomedical Event Extraction using Distant Supervision and Question Answering
Automatic extraction of event structures from text is a promising way to extract important facts from the evergrowing amount of biomedical literature. We propose BEEDS, a new approach on how to mine event structures from…
Event ExtractionKnowledge Base PopulationQuestion AnsweringA Generative Model for Relation Extraction and Classification
Relation extraction (RE) is an important information extraction task which provides essential information to many NLP applications such as knowledge base population and question answering. In this paper, we present a nov…
ClassificationKnowledge Base PopulationmodelQuestion Answering+3DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population. DeepKE implements various infor…
AttributeAttribute ExtractionCross-Domain Named Entity RecognitionKnowledge Base Population+4GenRE: A Generative Model for Relation Extraction
Relation extraction (RE) is an important information extraction task which provides essential information to many NLP applications such as knowledge base population and question answering. In this paper, we present a nov…
Knowledge Base PopulationmodelQuestion AnsweringRelation+2Set Generation Networks for End-to-End Knowledge Base Population
The task of knowledge base population (KBP) aims to discover facts about entities from texts and expand a knowledge base with these facts. Previous studies shape end-to-end KBP as a machine translation task, which is req…
DecoderKnowledge Base PopulationMachine TranslationSentenceEntity Linking Meets Deep Learning: Techniques and Solutions
Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base. EL plays an important role in the fields of knowledge engineering and data mining…
Deep LearningEntity LinkingKnowledge Base PopulationQuestion Answering+2Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset
Reasoning over commonsense knowledge bases (CSKB) whose elements are in the form of free-text is an important yet hard task in NLP. While CSKB completion only fills the missing links within the domain of the CSKB, CSKB p…
BenchmarkingKnowledge Base PopulationZero-shot Slot Filling with DPR and RAG
The ability to automatically extract Knowledge Graphs (KG) from a given collection of documents is a long-standing problem in Artificial Intelligence. One way to assess this capability is through the task of slot filling…
Knowledge Base PopulationKnowledge GraphsRAGRetrieval+4Deep Neural Networks for Relation Extraction
Relation extraction from text is an important task for automatic knowledge base population. In this thesis, we first propose a syntax-focused multi-factor attention network model for finding the relation between two enti…
DecoderJoint Entity and Relation ExtractionKnowledge Base PopulationRelation+1Biomedical Event Extraction as Multi-turn Question Answering
Biomedical event extraction from natural text is a challenging task as it searches for complex and often nested structures describing specific relationships between multiple molecular entities, such as genes, proteins, o…
Event ExtractionKnowledge Base PopulationLanguage ModelingLanguage Modelling+2Information Extraction of Clinical Trial Eligibility Criteria
Clinical trials predicate subject eligibility on a diversity of criteria ranging from patient demographics to food allergies. Trials post their requirements as semantically complex, unstructured free-text. Formalizing tr…
ClusteringDiversityEntity LinkingKnowledge Base Population+4PERLEX: A Bilingual Persian-English Gold Dataset for Relation Extraction
Relation extraction is the task of extracting semantic relations between entities in a sentence. It is an essential part of some natural language processing tasks such as information extraction, knowledge extraction, and…
Knowledge Base PopulationRelationRelation ExtractionSentence