Entity Extraction using GAN
21 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Entity Extraction using GAN
MedMentions
Most implemented papers
Real-time On-Demand Crowd-powered Entity Extraction
Output-agreement mechanisms such as ESP Game have been widely used in human computation to obtain reliable human-generated labels.
Tracking the Diffusion of Named Entities
Existing studies of how information diffuses across social networks have thus far concentrated on analysing and recovering the spread of deterministic innovations such as URLs, hashtags, and group membership.
A Practical Incremental Learning Framework For Sparse Entity Extraction
This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation.
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.
Transfer Learning for Entity Recognition of Novel Classes
Our results empirically demonstrate when each of the published approaches tends to do well.
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.
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science
This system meets computational information and knowledge management (CIKM) requirements of metadata-driven payload extraction, named entity extraction, and relationship extraction from text.
Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks
This paper contributes to solving problems related to ambiguity in PICO sentence prediction tasks, as well as highlighting how annotations for training named entity recognition systems are used to train a high-performing, but nevertheless flexible architecture for question answering in systematic review automation.
Common-Knowledge Concept Recognition for SEVA
We build a common-knowledge concept recognition system for a Systems Engineer's Virtual Assistant (SEVA) which can be used for downstream tasks such as relation extraction, knowledge graph construction, and question-answering.
Synchronous Double-channel Recurrent Network for Aspect-Opinion Pair Extraction
chenshaowei57/SDRN
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ACL 2020
The opinion entity extraction unit and the relation detection unit are developed as two channels to extract opinion entities and relations simultaneously.
