Entity Extraction using GAN Edit Task
Natural Language Processing
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Greatest papers with code
Revisiting Semi-Supervised Learning with Graph Embeddings
• tkipf/gcn
• 
We present a semi-supervised learning framework based on graph embeddings.
Ranked #1 on
Node Classification
on USA Air-Traffic
DOCUMENT CLASSIFICATION ENTITY EXTRACTION USING GAN NODE CLASSIFICATION
A Hierarchical Framework for Relation Extraction with Reinforcement Learning
The whole extraction process is decomposed into a hierarchy of two-level RL policies for relation detection and entity extraction respectively, so that it is more feasible and natural to deal with overlapping relations.
Ranked #2 on
Relation Extraction
on NYT24
ENTITY EXTRACTION USING GAN HIERARCHICAL REINFORCEMENT LEARNING RELATION EXTRACTION
A Unified MRC Framework for Named Entity Recognition
ACL 2020
• ShannonAI/mrc-for-flat-nested-ner
• 
Instead of treating the task of NER as a sequence labeling problem, we propose to formulate it as a machine reading comprehension (MRC) task.
Ranked #1 on
Named Entity Recognition
on ACE 2005
(using extra training data)
CHINESE NAMED ENTITY RECOGNITION ENTITY EXTRACTION USING GAN MACHINE READING COMPREHENSION NESTED MENTION RECOGNITION NESTED NAMED ENTITY RECOGNITION
CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning
The model is extremely weak at differing the head and tail entity, resulting in inaccurate entity extraction.
Ranked #8 on
Relation Extraction
on WebNLG
ENTITY EXTRACTION USING GAN MULTI-TASK LEARNING RELATION EXTRACTION
EATEN: Entity-aware Attention for Single Shot Visual Text Extraction
Extracting entity from images is a crucial part of many OCR applications, such as entity recognition of cards, invoices, and receipts.
Joint Extraction of Events and Entities within a Document Context
Events and entities are closely related; entities are often actors or participants in events and events without entities are uncommon.
Automatic Labeling for Entity Extraction in Cyber Security
Timely analysis of cyber-security information necessitates automated information extraction from unstructured text.
Transfer Learning for Entity Recognition of Novel Classes
Our results empirically demonstrate when each of the published approaches tends to do well.
ENTITY EXTRACTION USING GAN NAMED ENTITY RECOGNITION SENTIMENT ANALYSIS TRANSFER LEARNING
Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction
COLING 2016
• pgcool/TF-MTRNN
•
This paper proposes a novel context-aware joint entity and word-level relation extraction approach through semantic composition of words, introducing a Table Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the entity recognition and relation classification tasks to a table-filling problem and models their interdependencies.
ENTITY EXTRACTION USING GAN JOINT ENTITY AND RELATION EXTRACTION RELATION CLASSIFICATION SEMANTIC COMPOSITION STRUCTURED PREDICTION
Named Entity Recognition for Hindi-English Code-Mixed Social Media Text
Named Entity Recognition (NER) is a major task in the field of Natural Language Processing (NLP), and also is a sub-task of Information Extraction.