AraFinNLP 2024: The First Arabic Financial NLP Shared Task

Fuente: arXiv
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Autores principales: Malaysha, Sanad, El-Haj, Mo, Ezzini, Saad, Khalilia, Mohammed, Jarrar, Mustafa, Almujaiwel, Sultan, Berrada, Ismail, Bouamor, Houda
Formato: Preprint
Publicado: 2024
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author Malaysha, Sanad
El-Haj, Mo
Ezzini, Saad
Khalilia, Mohammed
Jarrar, Mustafa
Almujaiwel, Sultan
Berrada, Ismail
Bouamor, Houda
author_facet Malaysha, Sanad
El-Haj, Mo
Ezzini, Saad
Khalilia, Mohammed
Jarrar, Mustafa
Almujaiwel, Sultan
Berrada, Ismail
Bouamor, Houda
contents The expanding financial markets of the Arab world require sophisticated Arabic NLP tools. To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) shared task proposes two subtasks: (i) Multi-dialect Intent Detection and (ii) Cross-dialect Translation and Intent Preservation. This shared task uses the updated ArBanking77 dataset, which includes about 39k parallel queries in MSA and four dialects. Each query is labeled with one or more of a common 77 intents in the banking domain. These resources aim to foster the development of robust financial Arabic NLP, particularly in the areas of machine translation and banking chat-bots. A total of 45 unique teams registered for this shared task, with 11 of them actively participated in the test phase. Specifically, 11 teams participated in Subtask 1, while only 1 team participated in Subtask 2. The winning team of Subtask 1 achieved F1 score of 0.8773, and the only team submitted in Subtask 2 achieved a 1.667 BLEU score.
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id arxiv_https___arxiv_org_abs_2407_09818
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AraFinNLP 2024: The First Arabic Financial NLP Shared Task
Malaysha, Sanad
El-Haj, Mo
Ezzini, Saad
Khalilia, Mohammed
Jarrar, Mustafa
Almujaiwel, Sultan
Berrada, Ismail
Bouamor, Houda
Computation and Language
The expanding financial markets of the Arab world require sophisticated Arabic NLP tools. To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) shared task proposes two subtasks: (i) Multi-dialect Intent Detection and (ii) Cross-dialect Translation and Intent Preservation. This shared task uses the updated ArBanking77 dataset, which includes about 39k parallel queries in MSA and four dialects. Each query is labeled with one or more of a common 77 intents in the banking domain. These resources aim to foster the development of robust financial Arabic NLP, particularly in the areas of machine translation and banking chat-bots. A total of 45 unique teams registered for this shared task, with 11 of them actively participated in the test phase. Specifically, 11 teams participated in Subtask 1, while only 1 team participated in Subtask 2. The winning team of Subtask 1 achieved F1 score of 0.8773, and the only team submitted in Subtask 2 achieved a 1.667 BLEU score.
title AraFinNLP 2024: The First Arabic Financial NLP Shared Task
topic Computation and Language
url https://arxiv.org/abs/2407.09818