Named Entity Recognition (NER) is a key component in NLP systems for question
answering, information retrieval, relation extraction, etc. NER systems have been studied …

Abstract Named Entity Recognition (NER), one of the most fundamental problems in natural
language processing, seeks to identify the boundaries and types of entities with specific …

This paper presents an empirical study to efficiently build named entity recognition (NER)
systems when a small amount of in-domain labeled data is available. Based upon recent …

Sentiment analysis is a task of natural language processing that has recently attracted
increasing attention. However, sentiment analysis research has mainly been carried out for …

The aim of multi-output learning is to simultaneously predict multiple outputs given an input.
It is an important learning problem for decision-making since making decisions in the real …

Modern Arabic Sociolinguistics outlines and evaluates the major approaches and methods
used in Arabic sociolinguistic research with respect to diglossia, codeswitching, language …

In the recent past, more than 5 years or so, DL especially the large language models (LLMs)
has generated extensive studies out of a distinctly average downturn field of knowledge …

The explosion of online and offline data has changed how we gather, evaluate, and
understand data. It is frequently difficult and time-consuming to comprehend large text …

This paper presents Wojood, a corpus for Arabic nested Named Entity Recognition (NER).
Nested entities occur when one entity mention is embedded inside another entity mention …

As more and more Arabic texts emerged on the Internet, extracting important information
from these Arabic texts is especially useful. As a fundamental technology, Named entity …