Name: WikiANN
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

WikiANN

Lombard Language Training Dataset

Lombard Language Training Data

By wikiann (From Huggingface) [source]

About this dataset

Overview

WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus.

Columns

File: pdc_train.csv

Column name	Description
tokens	This column contains individual words or tokens in the Lombard language. (Text)
ner_tags	This column contains named entity recognition (NER) tags associated with each token. NER tags help identify and classify named entities such as names, locations, organizations, etc. (Text)
langs	This column indicates the language of each token. In this dataset, it specifically represents the Lombard language. (Text)
spans	This column provides information about the position or span of each token within the text. (Text)

File: sr_validation.csv

Column name	Description
tokens	This column contains individual words or tokens in the Lombard language. (Text)
ner_tags	This column contains named entity recognition (NER) tags associated with each token. NER tags help identify and classify named entities such as names, locations, organizations, etc. (Text)
langs	This column indicates the language of each token. In this dataset, it specifically represents the Lombard language. (Text)
spans	This column provides information about the position or span of each token within the text. (Text)

File: uz_train.csv

Column name	Description
tokens	This column contains individual words or tokens in the Lombard language. (Text)
ner_tags	This column contains named entity recognition (NER) tags associated with each token. NER tags help identify and classify named entities such as names, locations, organizations, etc. (Text)
langs	This column indicates the language of each token. In this dataset, it specifically represents the Lombard language. (Text)
spans	This column provides information about the position or span of each token within the text. (Text)

Research Ideas

Named Entity Recognition (NER) Training: The dataset can be used to train models for NER tasks specific to the Lombard language. By utilizing the ner_tags column, developers can create models that identify and classify named entities in Lombard text, such as names of people, places, organizations, and more.

Language Classification: Since the langs column indicates the language of each token in the dataset (which will always be Lombard), this dataset can be used for training language classification models. These models can then be utilized to automatically detect whether a given piece of text is in Lombard or another language.

Span Identification: The spans column provides information about the position or span of each token within the text. This information can be utilized to develop algorithms or applications that require analyzing specific spans within sentences or paragraphs in Lombard text. For example, it could help identify important phrases or extract certain sections of text from a larger document

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit wikiann (From Huggingface).

Tables

Ace Test

@kaggle.thedevastator_lombard_language_training_dataset.ace_test

11.42 KB
100 rows
4 columns


CREATE TABLE ace_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ace Train

@kaggle.thedevastator_lombard_language_training_dataset.ace_train

10.35 KB
100 rows
4 columns


CREATE TABLE ace_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ace Validation

@kaggle.thedevastator_lombard_language_training_dataset.ace_validation

10.96 KB
100 rows
4 columns


CREATE TABLE ace_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Af Test

@kaggle.thedevastator_lombard_language_training_dataset.af_test

79.85 KB
1000 rows
4 columns


CREATE TABLE af_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Af Train

@kaggle.thedevastator_lombard_language_training_dataset.af_train

342.88 KB
5000 rows
4 columns


CREATE TABLE af_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Af Validation

@kaggle.thedevastator_lombard_language_training_dataset.af_validation

81.31 KB
1000 rows
4 columns


CREATE TABLE af_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Als Test

@kaggle.thedevastator_lombard_language_training_dataset.als_test

14.9 KB
100 rows
4 columns


CREATE TABLE als_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Als Train

@kaggle.thedevastator_lombard_language_training_dataset.als_train

14.08 KB
100 rows
4 columns


CREATE TABLE als_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Als Validation

@kaggle.thedevastator_lombard_language_training_dataset.als_validation

14.01 KB
100 rows
4 columns


CREATE TABLE als_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Am Test

@kaggle.thedevastator_lombard_language_training_dataset.am_test

11.44 KB
100 rows
4 columns


CREATE TABLE am_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Am Train

@kaggle.thedevastator_lombard_language_training_dataset.am_train

10.79 KB
100 rows
4 columns


CREATE TABLE am_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Am Validation

@kaggle.thedevastator_lombard_language_training_dataset.am_validation

10.93 KB
100 rows
4 columns


CREATE TABLE am_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ang Test

@kaggle.thedevastator_lombard_language_training_dataset.ang_test

12.6 KB
100 rows
4 columns


CREATE TABLE ang_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ang Train

@kaggle.thedevastator_lombard_language_training_dataset.ang_train

12.33 KB
100 rows
4 columns


CREATE TABLE ang_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ang Validation

@kaggle.thedevastator_lombard_language_training_dataset.ang_validation

11.76 KB
100 rows
4 columns


CREATE TABLE ang_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

An Test

@kaggle.thedevastator_lombard_language_training_dataset.an_test

40.22 KB
1000 rows
4 columns


CREATE TABLE an_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

An Train

@kaggle.thedevastator_lombard_language_training_dataset.an_train

43.31 KB
1000 rows
4 columns


CREATE TABLE an_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

An Validation

@kaggle.thedevastator_lombard_language_training_dataset.an_validation

42.81 KB
1000 rows
4 columns


CREATE TABLE an_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Arc Test

@kaggle.thedevastator_lombard_language_training_dataset.arc_test

9.01 KB
100 rows
4 columns


CREATE TABLE arc_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Arc Train

@kaggle.thedevastator_lombard_language_training_dataset.arc_train

10.02 KB
100 rows
4 columns


CREATE TABLE arc_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Arc Validation

@kaggle.thedevastator_lombard_language_training_dataset.arc_validation

8.89 KB
100 rows
4 columns


CREATE TABLE arc_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ar Test

@kaggle.thedevastator_lombard_language_training_dataset.ar_test

606.16 KB
10000 rows
4 columns


CREATE TABLE ar_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ar Train

@kaggle.thedevastator_lombard_language_training_dataset.ar_train

1.13 MB
20000 rows
4 columns


CREATE TABLE ar_train (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Ar Validation

@kaggle.thedevastator_lombard_language_training_dataset.ar_validation

606.26 KB
10000 rows
4 columns


CREATE TABLE ar_validation (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);

Arz Test

@kaggle.thedevastator_lombard_language_training_dataset.arz_test

11.95 KB
100 rows
4 columns


CREATE TABLE arz_test (
  "tokens" VARCHAR,
  "ner_tags" VARCHAR,
  "langs" VARCHAR,
  "spans" VARCHAR
);