Repositorio de Datos de la UAM
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Código fuente Python - 21,8 KB - MD5: 374c17b2a2985c20a6a8d70ddf4c30b1
DataDatos
The participants could self-evaluate
Valores separados por comas - 1,3 MB - MD5: 69c7aca67096607d1c89aadfe991cc30
DataDatos
This file holds the majority of the dataset for participants to train their models.
Valores separados por comas - 1,0 MB - MD5: cb52147666ef9643fc65e73f02c536ca
DataDatos
This file is the final test for evaluation
Mar 27, 2025 - CLARA-FINT: Computational Linguistics Approaches to Readability and Automatic Simplification in Financial Narrative
Moreno-Sandoval, Antonio; Porta, Jordi; Carbajo-Coronado, Blanca, 2025, "Automatic financial term extractor", https://doi.org/10.21950/FWEML6, e-cienciaDatos, V1
The creation of this dataset is framed in the Spanish national project CLARA-FINT. The aim of this task within the project was to create an automatic financial term extractor for Spanish. In order to do so, the first step was to apply linguistic annotation on texts, namely annual reports from the main Spanish listed companies in the IBEX 35 index....
JSON - 983 B - MD5: f6a0893f8f7aeb98dbd4739991a27955
DataDatos
Desconocido - 636,2 MB - MD5: bbc6c03a45b2a118d7a59234f31994c5
DataDatos
Texto plano - 6,0 KB - MD5: 2b320a4a7317f5774a833ad4a5f0a19b
DocumentaciónDocumentation
Texto plano - 6,9 KB - MD5: 1269c065c4d4a3e641879528aeb24090
DocumentaciónDocumentation
JSON - 125 B - MD5: 29ba428df177361130afa82cf0883098
DataDatos
JSON - 309 B - MD5: 2c91eee35d8d31bbd0717317da254567
DataDatos
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