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

Showing 5175 of 170 papers

TitleStatusHype
A Multilingual Bag-of-Entities Model for Zero-Shot Cross-Lingual Text Classification0
Entity Type Prediction in Knowledge Graphs using Embeddings0
E2EET: From Pipeline to End-to-end Entity Typing via Transformer-Based Embeddings0
ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts0
Comprehensive Multi-Dataset Evaluation of Reading Comprehension0
Label Embedding for Zero-shot Fine-grained Named Entity Typing0
An Attentive Fine-Grained Entity Typing Model with Latent Type Representation0
Exploring the Combination of Contextual Word Embeddings and Knowledge Graph Embeddings0
Learning Entity Representations for Few-Shot Reconstruction of Wikipedia Categories0
Fine-Grained Chemical Entity Typing with Multimodal Knowledge Representation0
Interpretable Entity Representations through Large-Scale Typing0
Collective Learning From Diverse Datasets for Entity Typing in the Wild0
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification0
Divide and Denoise: Learning from Noisy Labels in Fine-Grained Entity Typing with Cluster-Wise Loss Correction0
A Multilingual Bag-of-Entities Model for Zero-Shot Cross-Lingual Text Classification0
Knowledge-Aware Conversational Semantic Parsing Over Web Tables0
Divide and Denoise: Learning from Noisy Labels in Fine-grained Entity Typing with Cluster-wise Loss Correction0
Description-Based Zero-shot Fine-Grained Entity Typing0
Building a Fine-Grained Entity Typing System Overnight for a New X (X = Language, Domain, Genre)0
All Entities are Not Created Equal: Examining the Long Tail for Fine-Grained Entity Typing0
Denoising Enhanced Distantly Supervised Ultrafine Entity Typing0
Annotation of Tense and Aspect Semantics for Sentential AMR0
From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification0
FINET: Context-Aware Fine-Grained Named Entity Typing0
Finer Grained Entity Typing with TypeNet0
Show:102550
← PrevPage 3 of 7Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MLMETF178.2Unverified
2K-Adapter ( fac-adapter )F177.69Unverified
3K-Adapter ( fac-adapter + lin-adapter )F177.61Unverified
4ERNIEF175.56Unverified
5MCCE-B (replicated by Adaseq)F152.1Unverified
6Prompt + NPCRF (replicated by Adaseq)F150.1Unverified
7UniST-LargeF149.9Unverified
8Prompt Learning (replicated by Adaseq))F149.3Unverified
9MLMETF149.1Unverified
10RoBERTa-Large + NPCRF (replicated by Adaseq)F147.3Unverified
#ModelMetricClaimedVerifiedStatus
1MLMETF149.1Unverified
2ELMo (distant denoising data)F140.2Unverified
3LabelGCN Xiong et al. (2019)F136.9Unverified
4Choi et al. (2018) w augmentationF132Unverified
#ModelMetricClaimedVerifiedStatus
1REXELAvg F196.01Unverified
2REXELAvg F190.93Unverified
3REXELAvg F186.74Unverified
#ModelMetricClaimedVerifiedStatus
1ReFinEDMicro-F184Unverified
#ModelMetricClaimedVerifiedStatus
1LITEMacro F180.1Unverified
#ModelMetricClaimedVerifiedStatus
1TextEnt-fullAccuracy37.4Unverified
#ModelMetricClaimedVerifiedStatus
1LITEMacro F186.6Unverified