Entity Typing
State-of-the-art leaderboards
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Greatest papers with code
ERNIE: Enhanced Language Representation with Informative Entities
ACL 2019
• thunlp/ERNIE
• 
Neural language representation models such as BERT pre-trained on large-scale corpora can well capture rich semantic patterns from plain text, and be fine-tuned to consistently improve the performance of various NLP tasks.
SOTA for Relation Extraction on FewRel
ENTITY TYPING KNOWLEDGE GRAPHS NATURAL LANGUAGE INFERENCE SENTIMENT ANALYSIS
BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languages
LREC 2018 • bheinzerling/bpemb
We present BPEmb, a collection of pre-trained subword unit embeddings in 275 languages, based on Byte-Pair Encoding (BPE).
Semantic Relation Classification via Bidirectional LSTM Networks with Entity-aware Attention using Latent Entity Typing
• roomylee/entity-aware-relation-classification
• 
Our model not only utilizes entities and their latent types as features effectively but also is more interpretable by visualizing attention mechanisms applied to our model and results of LET.
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
NAACL 2019
• xwhan/Extremely-Fine-Grained-Entity-Typing
•
Existing entity typing systems usually exploit the type hierarchy provided by knowledge base (KB) schema to model label correlations and thus improve the overall performance.
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding
Current systems of fine-grained entity typing use distant supervision in conjunction with existing knowledge bases to assign categories (type labels) to entity mentions.
Zero-Shot Open Entity Typing as Type-Compatible Grounding
We evaluate our system on a broad range of datasets, including standard fine-grained and coarse-grained entity typing datasets, and also a dataset in the biological domain.
Put It Back: Entity Typing with Language Model Enhancement
Entity typing aims to classify semantic types of an entity mention in a specific context.
ENTITY LINKING ENTITY TYPING LANGUAGE MODELLING QUESTION ANSWERING RELATION EXTRACTION
Fine-Grained Entity Typing in Hyperbolic Space
WS 2019
• nlpAThits/figet-hyperbolic-space
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How can we represent hierarchical information present in large type inventories for entity typing?
Representation Learning of Entities and Documents from Knowledge Base Descriptions
COLING 2018
• studio-ousia/textent
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In this paper, we describe TextEnt, a neural network model that learns distributed representations of entities and documents directly from a knowledge base (KB).