71 a 80 de 753 Resultados
Valores separados por comas - 61,6 KB -
MD5: ea437383a1cf773021dcd00dcd28215a
This file contains a sample dataset in CSV format with the cause-effect relationship |
Texto plano - 7,2 KB -
MD5: b3802f0c272c27752597cb58fd5058f4
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Texto plano - 7,9 KB -
MD5: b9c86c2d4c88fe29d54e72586a978095
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Adobe PDF - 2,4 MB -
MD5: 70185178d188dafbe5bcbd4c6cf6ae0e
This file summarizes the resources created during the CLARA-FINT project |
Código fuente Python - 21,8 KB -
MD5: 374c17b2a2985c20a6a8d70ddf4c30b1
The participants could self-evaluate |
Valores separados por comas - 1,3 MB -
MD5: 69c7aca67096607d1c89aadfe991cc30
This file holds the majority of the dataset for participants to train their models. |
Valores separados por comas - 1,0 MB -
MD5: cb52147666ef9643fc65e73f02c536ca
This file is the final test for evaluation |
27 mar 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... |
27 mar 2025 -
Automatic financial term extractor
JSON - 983 B -
MD5: f6a0893f8f7aeb98dbd4739991a27955
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27 mar 2025 -
Automatic financial term extractor
Desconocido - 636,2 MB -
MD5: bbc6c03a45b2a118d7a59234f31994c5
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