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

Eml Validation

@kaggle.thedevastator_lombard_language_training_dataset.eml_validation

14.34 KB
100 rows
4 columns


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

En Test

@kaggle.thedevastator_lombard_language_training_dataset.en_test

720.17 KB
10000 rows
4 columns


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

En Train

@kaggle.thedevastator_lombard_language_training_dataset.en_train

1.39 MB
20000 rows
4 columns


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

En Validation

@kaggle.thedevastator_lombard_language_training_dataset.en_validation

718.66 KB
10000 rows
4 columns


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

Eo Test

@kaggle.thedevastator_lombard_language_training_dataset.eo_test

519.05 KB
10000 rows
4 columns


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

Eo Train

@kaggle.thedevastator_lombard_language_training_dataset.eo_train

750.54 KB
15000 rows
4 columns


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

Eo Validation

@kaggle.thedevastator_lombard_language_training_dataset.eo_validation

524.49 KB
10000 rows
4 columns


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

Es Test

@kaggle.thedevastator_lombard_language_training_dataset.es_test

553.86 KB
10000 rows
4 columns


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

Es Train

@kaggle.thedevastator_lombard_language_training_dataset.es_train

1.05 MB
20000 rows
4 columns


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

Es Validation

@kaggle.thedevastator_lombard_language_training_dataset.es_validation

552.49 KB
10000 rows
4 columns


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

Et Test

@kaggle.thedevastator_lombard_language_training_dataset.et_test

678 KB
10000 rows
4 columns


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

Et Train

@kaggle.thedevastator_lombard_language_training_dataset.et_train

992.4 KB
15000 rows
4 columns


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

Et Validation

@kaggle.thedevastator_lombard_language_training_dataset.et_validation

682.66 KB
10000 rows
4 columns


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

Eu Test

@kaggle.thedevastator_lombard_language_training_dataset.eu_test

557.87 KB
10000 rows
4 columns


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

Eu Train

@kaggle.thedevastator_lombard_language_training_dataset.eu_train

569.58 KB
10000 rows
4 columns


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

Eu Validation

@kaggle.thedevastator_lombard_language_training_dataset.eu_validation

570.51 KB
10000 rows
4 columns


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

Ext Test

@kaggle.thedevastator_lombard_language_training_dataset.ext_test

12.76 KB
100 rows
4 columns


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

Ext Train

@kaggle.thedevastator_lombard_language_training_dataset.ext_train

11.25 KB
100 rows
4 columns


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

Ext Validation

@kaggle.thedevastator_lombard_language_training_dataset.ext_validation

13.53 KB
100 rows
4 columns


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

Fa Test

@kaggle.thedevastator_lombard_language_training_dataset.fa_test

546.6 KB
10000 rows
4 columns


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

Fa Train

@kaggle.thedevastator_lombard_language_training_dataset.fa_train

1.02 MB
20000 rows
4 columns


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

Fa Validation

@kaggle.thedevastator_lombard_language_training_dataset.fa_validation

554.38 KB
10000 rows
4 columns


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

Fi Test

@kaggle.thedevastator_lombard_language_training_dataset.fi_test

767.17 KB
10000 rows
4 columns


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

Fi Train

@kaggle.thedevastator_lombard_language_training_dataset.fi_train

1.47 MB
20000 rows
4 columns


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

Fiu Vro Test

@kaggle.thedevastator_lombard_language_training_dataset.fiu_vro_test

12.76 KB
100 rows
4 columns


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