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

Related tags

Deep LearningKIND
Overview

KIND (Kessler Italian Named-entities Dataset)

KIND is 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.

For the construction of the dataset, we decide to use texts available for free, under a license that permits both research and commercial use.

In particular we release four chapters with texts taken from: (i) Wikinews (WN) as a source of news texts belonging to the last decades; (ii) some Italian fiction books (FIC) whose authors died more than 70 years ago; (iii) writings and speeches from Italian politicians Aldo Moro (AM) and (iv) Alcide De Gasperi (ADG).

Wikinews

Wikinews is a multi-language free project of collaborative journalism. The Italian chapter contains more than 11,000 news articles, released under the Creative Commons Attribution 2.5 License.

In building KIND, we randomly choose 1,000 articles evenly distributed in the last 20 years, for a total of 308,622 tokens.

Literature

Regarding fiction literature, we annotate 86 book chapters taken from 10 books written by Italian authors, who all died more than 70 years ago, for a total of 192,448 tokens. The plain texts are taken from the Liber Liber website.

In particular, we choose: Il giorno delle Mésules (Ettore Castiglioni, 12,853 tokens), L'amante di Cesare (Augusto De Angelis, 13,464 tokens), Canne al vento (Grazia Deledda, 13,945 tokens), 1861-1911 - Cinquant’anni di vita nazionale ricordati ai fanciulli (Guido Fabiani, 10,801 tokens), Lettere dal carcere (Antonio Gramsci, 10,655), Anarchismo e democrazia (Errico Malatesta, 11,557 tokens), L'amore negato (Maria Messina, 31,115 tokens), La luna e i falò (Cesare Pavese, 10,705 tokens), La coscienza di Zeno (Italo Svevo, 56,364 tokens), Le cose piu grandi di lui (Luciano Zuccoli, 20,989 tokens).

In selecting works without copyright, we favored texts as recent as possible, so that the model trained on this data can be used efficiently on novels written in the last years, since the language used in these novels is more likely to be similar to the language used in the novels of our days.

Aldo Moro's Works

Writings belonging to Aldo Moro have recently been collected by the University of Bologna and published on a platform called Edizione Nazionale delle Opere di Aldo Moro.

The project is still ongoing and, by now, it contains 806 documents for a total of about one million tokens.

In the first release of KIND, we include 392,604 tokens from the Aldo Moro's works dataset, with silver annotations (see the reference below).

Alcide De Gasperi's Writings

Finally, we annotate 158 document (150,632 tokens) from Alcide Digitale, spanning 50 years of European history.

The complete corpus contains a comprehensive collection of Alcide De Gasperi’s public documents, 2,762 in total, written or transcribed between 1901 and 1954.

License

The NER annotations in (i), (ii), and (iii) are released under the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Annotation from Alcide De Gasperi's writings are released under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.

Owner
Digital Humanities
Digital Humanities Unit at Fondazione Bruno Kessler
Digital Humanities
Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.

Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline

12 Dec 02, 2022
A python code to convert Keras pre-trained weights to Pytorch version

Weights_Keras_2_Pytorch 最近想在Pytorch项目里使用一下谷歌的NIMA,但是发现没有预训练好的pytorch权重,于是整理了一下将Keras预训练权重转为Pytorch的代码,目前是支持Keras的Conv2D, Dense, DepthwiseConv2D, Batch

Liu Hengyu 2 Dec 16, 2021
An index of algorithms for learning causality with data

awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{

Ruocheng Guo 2.3k Jan 08, 2023
Advantage Actor Critic (A2C): jax + flax implementation

Advantage Actor Critic (A2C): jax + flax implementation Current version supports only environments with continious action spaces and was tested on muj

Andrey 3 Jan 23, 2022
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

Microsoft 5.7k Jan 09, 2023
A curated list of awesome resources combining Transformers with Neural Architecture Search

A curated list of awesome resources combining Transformers with Neural Architecture Search

Yash Mehta 173 Jan 03, 2023
Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)

Voxel-based Network for Shape Completion by Leveraging Edge Generation This is the PyTorch implementation for the paper "Voxel-based Network for Shape

10 Dec 04, 2022
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks

Adversarially-Robust-Periphery Code + Data from the paper "Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks" by A

Anne Harrington 2 Feb 07, 2022
Jupyter notebooks for using & learning Keras

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

ErhWen Kuo 2.1k Dec 27, 2022
particle tracking model, works with the ROMS output file(qck.nc, his.nc)

particle-tracking-model-for-ROMS particle tracking model, works with the ROMS output file(qck.nc, his.nc) description this is a 2-dimensional particle

xusheng 1 Jan 11, 2022
Code for the paper "Improving Vision-and-Language Navigation with Image-Text Pairs from the Web" (ECCV 2020)

Improving Vision-and-Language Navigation with Image-Text Pairs from the Web Arjun Majumdar, Ayush Shrivastava, Stefan Lee, Peter Anderson, Devi Parikh

Arjun Majumdar 44 Dec 14, 2022
Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks

This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi

Shunta Saito 255 Sep 07, 2022
PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks

AttentionHTR PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks. Scene Text

Dmitrijs Kass 31 Dec 22, 2022
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.

Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas

2.7k Jan 03, 2023
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

Antoine Caillon 589 Jan 02, 2023
Python script that allows you to automatically setup your Growtopia server.

AutoSetup Python script that allows you to automatically setup your Growtopia server. How To Use Firstly, install all the required modules that used i

Aspire 3 Mar 06, 2022
PyTorch implementation of neural style transfer algorithm

neural-style-pt This is a PyTorch implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias

770 Jan 02, 2023
An implementation of DeepMind's Relational Recurrent Neural Networks in PyTorch.

relational-rnn-pytorch An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch. Relational Memory Core (

Sang-gil Lee 241 Nov 18, 2022
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022
Pseudo-Visual Speech Denoising

Pseudo-Visual Speech Denoising This code is for our paper titled: Visual Speech Enhancement Without A Real Visual Stream published at WACV 2021. Autho

Sindhu 94 Oct 22, 2022