X Qu, Y Gu, Q Xia, Z Li, Z Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
Pre-trained language models (LMs) are currently integral to many natural language processing systems. Although multilingual LMs were also introduced to serve many …
Advancements in neural networks have led to developments in fields like computer vision, speech recognition and natural language processing (NLP). One of the most influential …
Abstract We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python. CAMeL Tools currently provides utilities for pre-processing …
With the evolution of the Internet and multimedia technology, the amount of text data has increased exponentially. This text volume is a precious source of information and knowledge …
Pretraining Bidirectional Encoder Representations from Transformers (BERT) for downstream NLP tasks is a non-trival task. We pretrained 5 BERT models that differ in the …
HW Yang, Y Zou, P Shi, W Lu, J Lin, X Sun - arXiv preprint arXiv …, 2019 - arxiv.org
Multilingual knowledge graphs (KGs), such as YAGO and DBpedia, represent entities in different languages. The task of cross-lingual entity alignment is to match entities in a source …
We present a deep hierarchical recurrent neural network for sequence tagging. Given a sequence of words, our model employs deep gated recurrent units on both character and …
O Kuru, OA Can, D Yuret - Proceedings of COLING 2016, the 26th …, 2016 - aclanthology.org
We describe and evaluate a character-level tagger for language-independent Named Entity Recognition (NER). Instead of words, a sentence is represented as a sequence of …