KIND: an Italian Multi-Domain Dataset for Named Entity Recognition

12/30/2021
by   Teresa Paccosi, et al.
0

In this paper we present KIND, an Italian dataset for Named-Entity Recognition. It contains more than one million tokens with the annotation covering three classes: persons, locations, and organizations. Most of the dataset (around 600K tokens) contains manual gold annotations in three different domains: news, literature, and political discourses. Texts and annotations are downloadable for free from the Github repository.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/26/2021

KazNERD: Kazakh Named Entity Recognition Dataset

We present the development of a dataset for Kazakh named entity recognit...
research
01/15/2019

A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection

Annotated datasets in different domains are critical for many supervised...
research
09/03/2019

Introducing RONEC -- the Romanian Named Entity Corpus

We present RONEC - the Named Entity Corpus for the Romanian language. Th...
research
09/11/2021

AdaK-NER: An Adaptive Top-K Approach for Named Entity Recognition with Incomplete Annotations

State-of-the-art Named Entity Recognition(NER) models rely heavily on la...
research
12/05/2019

Design and implementation of an open source Greek POS Tagger and Entity Recognizer using spaCy

This paper proposes a machine learning approach to part-of-speech taggin...
research
09/12/2015

Kannada named entity recognition and classification (nerc) based on multinomial naïve bayes (mnb) classifier

Named Entity Recognition and Classification (NERC) is a process of ident...
research
08/16/2021

Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss

We study learning named entity recognizers in the presence of missing en...

Please sign up or login with your details

Forgot password? Click here to reset