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

Arz Train

@kaggle.thedevastator_lombard_language_training_dataset.arz_train

12.6 KB
100 rows
4 columns


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

Arz Validation

@kaggle.thedevastator_lombard_language_training_dataset.arz_validation

12.01 KB
100 rows
4 columns


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

As Test

@kaggle.thedevastator_lombard_language_training_dataset.as_test

10.92 KB
100 rows
4 columns


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

As Train

@kaggle.thedevastator_lombard_language_training_dataset.as_train

11.46 KB
100 rows
4 columns


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

Ast Test

@kaggle.thedevastator_lombard_language_training_dataset.ast_test

53.12 KB
1000 rows
4 columns


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

Ast Train

@kaggle.thedevastator_lombard_language_training_dataset.ast_train

53.88 KB
1000 rows
4 columns


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

Ast Validation

@kaggle.thedevastator_lombard_language_training_dataset.ast_validation

52.19 KB
1000 rows
4 columns


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

As Validation

@kaggle.thedevastator_lombard_language_training_dataset.as_validation

11.8 KB
100 rows
4 columns


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

Ay Test

@kaggle.thedevastator_lombard_language_training_dataset.ay_test

6.74 KB
100 rows
4 columns


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

Ay Train

@kaggle.thedevastator_lombard_language_training_dataset.ay_train

7.36 KB
100 rows
4 columns


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

Ay Validation

@kaggle.thedevastator_lombard_language_training_dataset.ay_validation

6.81 KB
100 rows
4 columns


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

Az Test

@kaggle.thedevastator_lombard_language_training_dataset.az_test

81.41 KB
1000 rows
4 columns


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

Az Train

@kaggle.thedevastator_lombard_language_training_dataset.az_train

671.54 KB
10000 rows
4 columns


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

Az Validation

@kaggle.thedevastator_lombard_language_training_dataset.az_validation

81.76 KB
1000 rows
4 columns


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

Bar Test

@kaggle.thedevastator_lombard_language_training_dataset.bar_test

7.91 KB
100 rows
4 columns


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

Bar Train

@kaggle.thedevastator_lombard_language_training_dataset.bar_train

8.01 KB
100 rows
4 columns


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

Bar Validation

@kaggle.thedevastator_lombard_language_training_dataset.bar_validation

8.18 KB
100 rows
4 columns


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

Ba Test

@kaggle.thedevastator_lombard_language_training_dataset.ba_test

13.64 KB
100 rows
4 columns


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

Ba Train

@kaggle.thedevastator_lombard_language_training_dataset.ba_train

14.38 KB
100 rows
4 columns


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

Bat Smg Test

@kaggle.thedevastator_lombard_language_training_dataset.bat_smg_test

12.27 KB
100 rows
4 columns


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

Bat Smg Train

@kaggle.thedevastator_lombard_language_training_dataset.bat_smg_train

11.66 KB
100 rows
4 columns


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

Bat Smg Validation

@kaggle.thedevastator_lombard_language_training_dataset.bat_smg_validation

12.38 KB
100 rows
4 columns


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

Ba Validation

@kaggle.thedevastator_lombard_language_training_dataset.ba_validation

12.58 KB
100 rows
4 columns


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

Be Test

@kaggle.thedevastator_lombard_language_training_dataset.be_test

82.15 KB
1000 rows
4 columns


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

Be Train

@kaggle.thedevastator_lombard_language_training_dataset.be_train

970.99 KB
15000 rows
4 columns


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