README.md

---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license: cc-by-4.0
multilinguality:
- monolingual
pretty_name: ceil
size_categories:
- unknown
source_datasets: []
task_ids: []
---

# Dataset Card for CEIL
 
## Dataset Description
- **Homepage** [Projecte AINA](https://projecteaina.cat/tech/)
- **Repository** [HuggingFace](https://huggingface.co/projecte-aina)
- **Point of Contact** langtech@bsc.es


### Dataset Summary

Catalan Entity Identification and Linking (CEIL) is a dataset for complex Named Entity Recognition (NER) created by the AINA project in the BSC for Machine Learning and Language Model evaluation purposes in Catalan. 
It contains 9 main types and 52 subtypes on all kinds of short texts, with almost 59K documents. 


![Prodigy Example](https://huggingface.co/datasets/crodri/ceil/resolve/main/Selection_021.png "Prodigy Example")

### Supported Tasks and Leaderboards

Named Entities Recognition, Language Model

### Languages

The dataset is in Catalan (`ca-ES`).

## Dataset Structure

### Data Instances

Three two-column files, one for each split. 

<pre>
l'      O
obra    O
de      O
Galileu B-person-scholar/scientist
,       O
i       O
de      O
la      O
multiplicació   O
de      O
les     O
acadèmies       O
científiques    O
,       O
com     O
l'      O
Accademia       B-organization-education
dei     I-organization-education
Lincei  I-organization-education
</pre>

### Data Fields

Every file has two columns, with the word form or punctuation symbol in the first one and the corresponding IOB tag in the second one.

### Data Splits

80/20 Train and development sets, balanced for all NERC tags. Test set incloudes documents that contain overall all the possible types in the corpus.


## Dataset Creation

### Curation Rationale

We created this corpus to contribute to the development of language models in Catalan.

### Source Data

#### Initial Data Collection and Normalization

Documents were gathered from various online sources:

- Tweets about different topics, such as catalan independence, coronavirus, benidormfest, vaccines, etc.
- Newswire from nacio digital (Motor) Vilaweb (opinion pieces), Agencia Catalana de Noticies (Economy and Memoria Histórica)
- Various threads from Raco Catalá forum
- Viquipedia articles (woman bios, film synopses, etc.)
- OTHER: Parliament proceedings, restaurant online reviews, etc.

The word tokenization used to convert offset annotations into CONLL files was done using spacy

#### Who are the source language producers?

The original data comes from various sources.

### Annotations

#### Annotation process

We adapted the NER labels from  to a token-per-line, multi-column format. 

#### Who are the annotators?

The annotation was entrusted to the company M47 labs through a public tender process.

Guidelines available at [Zenodo](https://doi.org/10.5281/zenodo.8318188)

### Personal and Sensitive Information

No personal or sensitive information included.

## Considerations for Using the Data

### Social Impact of Dataset

We hope this corpus contributes to the development of language models in Catalan, a low-resource language.

### Discussion of Biases

[N/A]

### Other Known Limitations

[N/A]

## Additional Information

### Dataset Curators

Language Technologies Unit at the Barcelona Supercomputing Center (langtech@bsc.es).

This work has been promoted and financed by the Generalitat de Catalunya through the [Aina project](https://projecteaina.cat/).


### Licensing Information

CEIL is used under [CC-by](https://creativecommons.org/licenses/by/4.0/) licence. 

### Citation Information

```
@inproceedings{gonzalez-agirre-etal-2024-building-data,
    title = "Building a Data Infrastructure for a Mid-Resource Language: The Case of {C}atalan",
    author = "Gonzalez-Agirre, Aitor  and
      Marimon, Montserrat  and
      Rodriguez-Penagos, Carlos  and
      Aula-Blasco, Javier  and
      Baucells, Irene  and
      Armentano-Oller, Carme  and
      Palomar-Giner, Jorge  and
      Kulebi, Baybars  and
      Villegas, Marta",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.231",
    pages = "2556--2566",
}

```


### Contributions

[N/A]