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Our research explores the use of natural language processing (NLP) methods to automatically classify entities for the purpose of knowledge graph population and integration with food system ontologies. We have created NLP models that can…

Transcribed speech and user-generated text in Arabic typically contain a mixture of Modern Standard Arabic (MSA), the standardized language taught in schools, and Dialectal Arabic (DA), used in daily communications. To handle this…

Computation and Language · Computer Science 2023-10-24 Amr Keleg , Sharon Goldwater , Walid Magdy

We present Qabas, a novel open-source Arabic lexicon designed for NLP applications. The novelty of Qabas lies in its synthesis of 110 lexicons. Specifically, Qabas lexical entries (lemmas) are assembled by linking lemmas from 110 lexicons.…

Computation and Language · Computer Science 2024-06-12 Mustafa Jarrar , Tymaa Hammouda

The rapid advancements in Large Language Models (LLMs) have led to significant improvements in various natural language processing tasks. However, the evaluation of LLMs' legal knowledge, particularly in non-English languages such as…

Natural Language Inference (NLI) is a hot topic research in natural language processing, contradiction detection between sentences is a special case of NLI. This is considered a difficult NLP task which has a big influence when added as a…

Computation and Language · Computer Science 2023-04-05 Khloud Al Jallad , Nada Ghneim

The Arabic language is a morphologically rich language with relatively few resources and a less explored syntax compared to English. Given these limitations, Arabic Natural Language Processing (NLP) tasks like Sentiment Analysis (SA), Named…

Computation and Language · Computer Science 2021-03-09 Wissam Antoun , Fady Baly , Hazem Hajj

Arabic morphological analysis is one of the essential stages in Arabic Natural Language Processing. In this paper we present an approach for Arabic morphological analysis. This approach is based on Arabic morphological automaton (AMAUT).…

Computation and Language · Computer Science 2011-01-31 Mourad Gridach , Noureddine Chenfour

Parallel texts are a relatively rare language resource, however, they constitute a very useful research material with a wide range of applications. This study presents and analyses new methodologies we developed for obtaining such data from…

Computation and Language · Computer Science 2016-03-23 Krzysztof Wołk , Emilia Rejmund , Krzysztof Marasek

The rapid growth of the internet has increased the number of online texts. This led to the rapid growth of the number of online texts in the Arabic language. The enormous amount of text must be organized into classes to make the analysis…

Information Retrieval · Computer Science 2022-11-08 Sumaia Mohammed AL-Ghuribi , Shahrul Azman Mohd Noah

Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the…

Computation and Language · Computer Science 2015-10-27 Kais Dukes

Large language models (LLMs) have greatly impacted the natural language processing (NLP) field, particularly for the English language. These models have demonstrated capabilities in understanding and generating human-like text. The success…

Computation and Language · Computer Science 2024-07-10 Hasna Chouikhi , Manel Aloui , Cyrine Ben Hammou , Ghaith Chaabane , Haithem Kchaou , Chehir Dhaouadi

The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design. This distinguishes natural languages such as Arabic and Japanese from artificially…

Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introducing seven synthetic datasets in dialects alongside Modern…

Computation and Language · Computer Science 2024-12-19 Basel Mousi , Nadir Durrani , Fatema Ahmad , Md. Arid Hasan , Maram Hasanain , Tameem Kabbani , Fahim Dalvi , Shammur Absar Chowdhury , Firoj Alam

This work presents a novel framework for training Arabic nested embedding models through Matryoshka Embedding Learning, leveraging multilingual, Arabic-specific, and English-based models, to highlight the power of nested embeddings models…

Computation and Language · Computer Science 2024-08-02 Omer Nacar , Anis Koubaa

We release Galactic Dependencies 1.0---a large set of synthetic languages not found on Earth, but annotated in Universal Dependencies format. This new resource aims to provide training and development data for NLP methods that aim to adapt…

Computation and Language · Computer Science 2017-10-12 Dingquan Wang , Jason Eisner

Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in high-resource languages. However, the performance of MT…

Computation and Language · Computer Science 2024-03-29 Atnafu Lambebo Tonja , Olga Kolesnikova , Alexander Gelbukh , Jugal Kalita

Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dialectal Arabic varieties, notably Egyptian Arabic, have…

Computation and Language · Computer Science 2016-09-13 Salam Khalifa , Nizar Habash , Dana Abdulrahim , Sara Hassan

Existing discourse corpora are annotated based on different frameworks, which show significant dissimilarities in definitions of arguments and relations and structural constraints. Despite surface differences, these frameworks share basic…

Computation and Language · Computer Science 2024-04-09 Yingxue Fu

The global deployment of large language models (LLMs) has raised concerns about cultural misalignment, yet the linguistic properties of fine-tuning datasets used for cultural adaptation remain poorly understood. We adopt a dataset-centric…

Computation and Language · Computer Science 2026-02-03 Reem I. Masoud , Chen Feng , Shunta Asano , Saied Alshahrani , Philip Colin Treleaven , Miguel R. D. Rodrigues