Spanish Learner Text Corpus for Classification Models

Encompassing texts from students of Spanish as a Foreign Language (ELE), sourced from the CAES corpus of the Instituto Cervantes. Its primary objective is to create and train a deep learning classification model based on these learner texts.

Use Cases

• Train a text classification model to categorize learner texts by proficiency level or error type.
• Analyze linguistic patterns and common errors in Spanish learner texts from the CAES corpus.
• Fine-tune a language model on Spanish as a Foreign Language (ELE) student writing for educational applications.

Strengths

• Dataset is derived from the CAES corpus, an established resource from the Instituto Cervantes.
• Tagged with a size category of 10K<n<100K, indicating a moderate scale.

Limitations

• Specific column names, row count, and data format are unknown, limiting immediate usability.
• The dataset's geographic and temporal coverage for the learner texts is unspecified.

Provenance

Source

CAES (Corpus de Aprendices de Español como Lengua Extranjera) from the Instituto Cervantes website.

Collection Method

Compiled from a set of files downloaded from the CAES corpus.

Freshness

Last updated on 2022-07-06.