Example-Based Named Entity Recognition

08/24/2020
by   Morteza Ziyadi, et al.
0

We present a novel approach to named entity recognition (NER) in the presence of scarce data that we call example-based NER. Our train-free few-shot learning approach takes inspiration from question-answering to identify entity spans in a new and unseen domain. In comparison with the current state-of-the-art, the proposed method performs significantly better, especially when using a low number of support examples.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/08/2023

MphayaNER: Named Entity Recognition for Tshivenda

Named Entity Recognition (NER) plays a vital role in various Natural Lan...
research
11/30/2021

KARL-Trans-NER: Knowledge Aware Representation Learning for Named Entity Recognition using Transformers

The inception of modeling contextual information using models such as BE...
research
05/22/2023

Taxonomy Expansion for Named Entity Recognition

Training a Named Entity Recognition (NER) model often involves fixing a ...
research
11/27/2022

PUnifiedNER: a Prompting-based Unified NER System for Diverse Datasets

Much of named entity recognition (NER) research focuses on developing da...
research
05/27/2016

Boosting Question Answering by Deep Entity Recognition

In this paper an open-domain factoid question answering system for Polis...
research
05/27/2021

Neural Entity Recognition with Gazetteer based Fusion

Incorporating external knowledge into Named Entity Recognition (NER) sys...
research
11/15/2021

Zero-Shot Learning in Named-Entity Recognition with External Knowledge

A significant shortcoming of current state-of-the-art (SOTA) named-entit...

Please sign up or login with your details

Forgot password? Click here to reset