Universidad Autónoma de Madrid

Repositorio de Datos de la UAM

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2,631 to 2,640 of 3,315 Results

readme_en.txt Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Texto plano - 7,2 KB - MD5: b3802f0c272c27752597cb58fd5058f4 DocumentaciónDocumentation
readme_es.txt Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Texto plano - 7,9 KB - MD5: b9c86c2d4c88fe29d54e72586a978095 DocumentaciónDocumentation
resources.pdf Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Adobe PDF - 2,4 MB - MD5: 70185178d188dafbe5bcbd4c6cf6ae0e DocumentaciónDocumentation This file summarizes the resources created during the CLARA-FINT project
task_evaluate.py Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Código fuente Python - 21,8 KB - MD5: 374c17b2a2985c20a6a8d70ddf4c30b1 DataDatos The participants could self-evaluate
test_subtask_es.csv Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Valores separados por comas - 1,3 MB - MD5: 69c7aca67096607d1c89aadfe991cc30 DataDatos This file holds the majority of the dataset for participants to train their models.
training_subtask_es.csv Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset Valores separados por comas - 1,0 MB - MD5: cb52147666ef9643fc65e73f02c536ca DataDatos This file is the final test for evaluation
Automatic financial term extractor 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....
config.json Mar 27, 2025 - Automatic financial term extractor JSON - 983 B - MD5: f6a0893f8f7aeb98dbd4739991a27955 DataDatos
pytorch_model.bin Mar 27, 2025 - Automatic financial term extractor Desconocido - 636,2 MB - MD5: bbc6c03a45b2a118d7a59234f31994c5 DataDatos
readme_en.txt Mar 27, 2025 - Automatic financial term extractor Texto plano - 6,0 KB - MD5: 2b320a4a7317f5774a833ad4a5f0a19b DocumentaciónDocumentation

readme_en.txt

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Texto plano - 7,2 KB -

DocumentaciónDocumentation

readme_es.txt

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Texto plano - 7,9 KB -

DocumentaciónDocumentation

resources.pdf

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Adobe PDF - 2,4 MB -

DocumentaciónDocumentation

This file summarizes the resources created during the CLARA-FINT project

task_evaluate.py

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Código fuente Python - 21,8 KB -

DataDatos

The participants could self-evaluate

test_subtask_es.csv

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Valores separados por comas - 1,3 MB -

DataDatos

This file holds the majority of the dataset for participants to train their models.

training_subtask_es.csv

Mar 27, 2025 - The financial document causality detection shared task (FinCausal 2023): Dataset

Valores separados por comas - 1,0 MB -

DataDatos

This file is the final test for evaluation

Automatic financial term extractor

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....

config.json

Mar 27, 2025 - Automatic financial term extractor

JSON - 983 B -

DataDatos

pytorch_model.bin

Mar 27, 2025 - Automatic financial term extractor

Desconocido - 636,2 MB -

DataDatos

readme_en.txt

Mar 27, 2025 - Automatic financial term extractor

Texto plano - 6,0 KB -

DocumentaciónDocumentation

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