5.801 a 5.810 de 6.831 Resultados
Adobe PDF - 221,2 KB -
MD5: 62d2718538183d7eb14bff92072b4b5c
The corresponding PDF file with the main publication of the competition (2023) |
Texto plano - 8,4 KB -
MD5: 4db8ecbe9182ff19a7e71a5ea768685f
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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; 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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Texto plano - 4,3 KB -
MD5: d15a8a67f8d14024ba208c48f3481a6e
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Binario Stata 14 - 114,3 MB -
MD5: 7afe66d0d71642cd1692d00a6d4ea929
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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.... |
