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Found 30 papers, 3 papers with code
SinaTools: Open Source Toolkit for Arabic Natural Language Processing
We introduce SinaTools, an open-source Python package for Arabic natural language processing and understanding.
Casablanca: Data and Models for Multidialectal Arabic Speech Recognition
In spite of the recent progress in speech processing, the majority of world languages and dialects remain uncovered.
Event-Arguments Extraction Corpus and Modeling using BERT for Arabic
Additionally, we propose a novel method for event relation extraction using BERT, in which we treat the task as text entailment.
ArabicNLU 2024: The First Arabic Natural Language Understanding Shared Task
This paper presents an overview of the Arabic Natural Language Understanding (ArabicNLU 2024) shared task, focusing on two subtasks: Word Sense Disambiguation (WSD) and Location Mention Disambiguation (LMD).
The FIGNEWS Shared Task on News Media Narratives
The shared task addresses bias and propaganda annotation in multilingual news posts.
AraFinNLP 2024: The First Arabic Financial NLP Shared Task
Specifically, 11 teams participated in Subtask 1, while only 1 team participated in Subtask 2.
WojoodNER 2024: The Second Arabic Named Entity Recognition Shared Task
The winning teams achieved F-1 scores of 91% and 92% in the Flat Fine-Grained and Nested Fine-Grained Subtasks, respectively.
Sina at FigNews 2024: Multilingual Datasets Annotated with Bias and Propaganda
The proliferation of bias and propaganda on social media is an increasingly significant concern, leading to the development of techniques for automatic detection.
Qabas: An Open-Source Arabic Lexicographic Database
Compared with other lexicons, Qabas stands as the most extensive Arabic lexicon, encompassing about 58K lemmas (45K nominal lemmas, 12. 5K verbal lemmas, and 473 functional-word lemmas).
Are Large Language Models the New Interface for Data Pipelines?
A Language Model is a term that encompasses various types of models designed to understand and generate human communication.
NLU-STR at SemEval-2024 Task 1: Generative-based Augmentation and Encoder-based Scoring for Semantic Textual Relatedness
Semantic textual relatedness is a broader concept of semantic similarity.
ArBanking77: Intent Detection Neural Model and a New Dataset in Modern and Dialectical Arabic
This paper presents the ArBanking77, a large Arabic dataset for intent detection in the banking domain.
SALMA: Arabic Sense-Annotated Corpus and WSD Benchmarks
To establish a Word Sense Disambiguation baseline using our SALMA corpus, we developed an end-to-end Word Sense Disambiguation system using Target Sense Verification.
Arabic Fine-Grained Entity Recognition
To compute the baselines of WojoodF ine, we fine-tune three pre-trained Arabic BERT encoders in three settings: flat NER, nested NER and nested NER with subtypes and achieved F1 score of 0. 920, 0. 866, and 0. 885, respectively.
Nabra: Syrian Arabic Dialects with Morphological Annotations
This paper presents Nabra, a corpora of Syrian Arabic dialects with morphological annotations.
WojoodNER 2023: The First Arabic Named Entity Recognition Shared Task
The winning teams achieved F1 scores of 91. 96 and 93. 73 in FlatNER and NestedNER, respectively.
Offensive Hebrew Corpus and Detection using BERT
Fine-tuning AlephBERT on our data and testing on D_OLaH yields 69% accuracy, while fine-tuning on D_OLaH and testing on our data yields 57% accuracy, which may be an indication to the generalizability our data offers.
Context-Gloss Augmentation for Improving Arabic Target Sense Verification
The most common semantically-labeled dataset for Arabic is the ArabGlossBERT, a relatively small dataset that consists of 167K context-gloss pairs (about 60K positive and 107K negative pairs), collected from Arabic dictionaries.
A Benchmark and Scoring Algorithm for Enriching Arabic Synonyms
Our proposed algorithm extracts synonyms from existing lexicons and computes a fuzzy value for each candidate.
Lisan: Yemeni, Iraqi, Libyan, and Sudanese Arabic Dialect Copora with Morphological Annotations
This article presents morphologically-annotated Yemeni, Sudanese, Iraqi, and Libyan Arabic dialects Lisan corpora.
Current Trends and Approaches in Synonyms Extraction: Potential Adaptation to Arabic
The third approach is to construct new WordNets by exploring synonymy graphs, and the fourth approach is to find similar words from corpora using Deep Learning methods, such as word embeddings and recently BERT models.
Wojood: Nested Arabic Named Entity Corpus and Recognition using BERT
This paper presents Wojood, a corpus for Arabic nested Named Entity Recognition (NER).
Curras + Baladi: Towards a Levantine Corpus
This is due to many factors, including the complex and rich morphology of Arabic, its high degree of ambiguity, and the presence of several regional varieties that need to be processed while taking into account their unique characteristics.
ArabGlossBERT: Fine-Tuning BERT on Context-Gloss Pairs for WSD
First, we constructed a dataset of labeled Arabic context-gloss pairs (~167k pairs) we extracted from the Arabic Ontology and the large lexicographic database available at Birzeit University.
The Arabic Ontology -- An Arabic Wordnet with Ontologically Clean Content
The ontology provides a formal representation of the concepts that the Arabic terms convey, and its content was built with ontological analysis in mind, and benchmarked to scientific advances and rigorous knowledge sources as much as this is possible, rather than to only speakers' beliefs as lexicons typically are.
LU-BZU at SemEval-2021 Task 2: Word2Vec and Lemma2Vec performance in Arabic Word-in-Context disambiguation
This paper presents a set of experiments to evaluate and compare between the performance of using CBOW Word2Vec and Lemma2Vec models for Arabic Word-in-Context (WiC) disambiguation without using sense inventories or sense embeddings.
Extracting Synonyms from Bilingual Dictionaries
We present our progress in developing a novel algorithm to extract synonyms from bilingual dictionaries.
A Panoramic Survey of Natural Language Processing in the Arab World
The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design.
