SOTAVerified

Entity Typing

Entity Typing is an important task in text analysis. Assigning types (e.g., person, location, organization) to mentions of entities in documents enables effective structured analysis of unstructured text corpora. The extracted type information can be used in a wide range of ways (e.g., serving as primitives for information extraction and knowledge base (KB) completion, and assisting question answering). Traditional Entity Typing systems focus on a small set of coarse types (typically fewer than 10). Recent studies work on a much larger set of fine-grained types which form a tree-structured hierarchy (e.g., actor as a subtype of artist, and artist is a subtype of person).

Source: Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

Image Credit: Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding

Papers

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Showing 101–150 of 170 papers

TitleStatusHype
Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and RecognitionCode0
Prompt-Learning for Fine-Grained Entity Typing—0
Manifold Alignment across Geometric Spaces for Knowledge Base Representation LearningCode0
Fine-grained General Entity Typing in German using GermaNetCode0
ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation ExtractionCode0
LOME: Large Ontology Multilingual Extraction—0
FGNET-RH: Fine-Grained Named Entity Typing via Refinement in Hyperbolic Space—0
ManyEnt: A Dataset for Few-shot Entity TypingCode0
Simple Hierarchical Multi-Task Neural End-To-End Entity Linking for Biomedical Text—0
ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts—0
Zero-Shot Learning with Common Sense Knowledge Graphs—0
Interpretable Entity Representations through Large-Scale Typing—0
Entity Type Prediction in Knowledge Graphs using Embeddings—0
Exploring the Combination of Contextual Word Embeddings and Knowledge Graph Embeddings—0
Fine-Grained Named Entity Typing over Distantly Supervised Data Based on Refined Representations—0
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing—0
E2EET: From Pipeline to End-to-end Entity Typing via Transformer-Based Embeddings—0
Exploiting Semantic Relations for Fine-grained Entity TypingCode0
ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension—0
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model—0
A Primal Dual Formulation For Deep Learning With ConstraintsCode0
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
An Attentive Fine-Grained Entity Typing Model with Latent Type Representation—0
Comprehensive Multi-Dataset Evaluation of Reading Comprehension—0
Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks—0
Redcoat: A Collaborative Annotation Tool for Hierarchical Entity Typing—0
MTab: Matching Tabular Data to Knowledge Graph using Probability ModelsCode0
Improving Fine-grained Entity Typing with Entity LinkingCode0
On the Importance of Subword Information for Morphological Tasks in Truly Low-Resource Languages—0
Fine-Grained Entity Typing for Domain Independent Entity LinkingCode0
Knowledge Enhanced Contextual Word RepresentationsCode0
Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification—0
EntEval: A Holistic Evaluation Benchmark for Entity RepresentationsCode0
Zero-Shot Open Entity Typing as Type-Compatible GroundingCode0
KCAT: A Knowledge-Constraint Typing Annotation ToolCode0
Fine-Grained Entity Typing in Hyperbolic SpaceCode0
Description-Based Zero-shot Fine-Grained Entity Typing—0
ERNIE: Enhanced Language Representation with Informative EntitiesCode0
Learning to Denoise Distantly-Labeled Data for Entity TypingCode0
A Systematic Study of Leveraging Subword Information for Learning Word RepresentationsCode0
Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering—0
Learning Entity Representations for Few-Shot Reconstruction of Wikipedia Categories—0
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity TypingCode0
Semantic Relation Classification via Bidirectional LSTM Networks with Entity-aware Attention using Latent Entity TypingCode0
Multi-Multi-View Learning: Multilingual and Multi-Representation Entity TypingCode0
Collective Learning From Diverse Datasets for Entity Typing in the Wild—0
Put It Back: Entity Typing with Language Model EnhancementCode0
Knowledge-Aware Conversational Semantic Parsing Over Web Tables—0
Attributed and Predictive Entity Embedding for Fine-Grained Entity Typing in Knowledge BasesCode0
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All datasetsOpen EntityOntonotes v5 (English)DocRED-IEAIDA-CoNLLFIGERFreebase FIGEROntoNotes

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MLMETF178.2—Unverified
2K-Adapter ( fac-adapter )F177.69—Unverified
3K-Adapter ( fac-adapter + lin-adapter )F177.61—Unverified
4ERNIEF175.56—Unverified
5MCCE-B (replicated by Adaseq)F152.1—Unverified
6Prompt + NPCRF (replicated by Adaseq)F150.1—Unverified
7UniST-LargeF149.9—Unverified
8Prompt Learning (replicated by Adaseq)）F149.3—Unverified
9MLMETF149.1—Unverified
10RoBERTa-Large + NPCRF (replicated by Adaseq)F147.3—Unverified
#ModelMetricClaimedVerifiedStatus
1MLMETF149.1—Unverified
2ELMo (distant denoising data)F140.2—Unverified
3LabelGCN Xiong et al. (2019)F136.9—Unverified
4Choi et al. (2018) w augmentationF132—Unverified
#ModelMetricClaimedVerifiedStatus
1REXELAvg F196.01—Unverified
2REXELAvg F190.93—Unverified
3REXELAvg F186.74—Unverified
#ModelMetricClaimedVerifiedStatus
1ReFinEDMicro-F184—Unverified
#ModelMetricClaimedVerifiedStatus
1LITEMacro F180.1—Unverified
#ModelMetricClaimedVerifiedStatus
1TextEnt-fullAccuracy37.4—Unverified
#ModelMetricClaimedVerifiedStatus
1LITEMacro F186.6—Unverified