61 a 70 de 758 Resultados
Texto plano - 9,1 KB -
MD5: 0c6967e12380fe519d8a4ee7416b9c17
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Adobe PDF - 2,4 MB -
MD5: 70185178d188dafbe5bcbd4c6cf6ae0e
This file summarizes the resources created during the CLARA-FINT project |
Moreno-Sandoval, Antonio; Carbajo-Coronado, Blanca, 2025, "The financial narrative summarisation shared task (FNS 2022 & 2023): Datasets", https://doi.org/10.21950/WRH0SO, e-cienciaDatos, V1
Financial Narrative Processing (FNP) consists of workshops organized by Lancaster University at international NLP conferences to address various aspects of automatic processing of financial narratives, including automatic summarization. The LLI-UAM participated in 2022 and 2023 b... |
Archivo ZIP - 19,4 MB -
MD5: b2fce792b642bfeab879842ce2ed977d
It contains three subfolders. Each corresponds to a phase of the competition and development by the participants |
Moreno-Sandoval, Antonio; Porta, Jordi; García Toro, Ana, 2025, "Discourse markers: Annotation guidelines", https://doi.org/10.21950/NWANNV, e-cienciaDatos, V1
This work is framed in the Spanish national project CLARA-FINT. The aim of this task within the project was to create an automatic discourse markers extractor for Spanish. In order to do so, the first step was to create these Annotation Guidelines to apply linguistic annotation o... |
28 mar 2025 -
Discourse markers: Annotation guidelines
Adobe PDF - 1,5 MB -
MD5: fe6b366cc4ff31661a29c10d085801d8
The annotation guideline document |
28 mar 2025 -
Discourse markers: Annotation guidelines
Texto plano - 4,7 KB -
MD5: e14469b96ad01eb60617f1db7b14c633
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Moreno-Sandoval, Antonio; Carbajo-Coronado, Blanca; Porta, Jordi, 2025, "The financial document causality detection shared task (FinCausal 2023): Dataset", https://doi.org/10.21950/2JOAZJ, e-cienciaDatos, V1
The Financial Document Causality Detection Task (FinCausal 2023) aims at improving the causality in the financial domain trough its texts. Participants are asked to identify, in causal sentences, which elements of the sentence relate to the cause, and which relate to the effect.... |
Adobe PDF - 170,4 KB -
MD5: 729bda5f1f32ca607adf583308a302a2
This file contains everything needed to start the task, as well as the annotation guidelines that served as a reference for the linguists to annotate the causality and thus generate the competition dataset. |
Adobe PDF - 125,4 KB -
MD5: e58a3a10790ab3a30c597e61f292ea4b
The main paper of the competition. |
