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May 10, 2024 · Abstract. This paper presents the winning solution to the Arabic Named Entity Recognition challenge run by Topcoder.com. The proposed model integrates various tailored techniques together, including representation learning, feature engineering, sequence labeling, and ensemble learning.
- Liyuan Liu, Jingbo Shang, Jiawei Han
- 2019
Feb 7, 2023 · A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends. 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 recognition (NER) serves as the core component in information extraction technology ...
- arXiv:2302.03512 [cs.CL]
- Computation and Language (cs.CL)
- Accepted by IEEE TKDE
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What is the winning solution to the Arabic Named Entity Recognition Challenge?
What is name entity recognition?
Is Arabic NER better than other deep learning methods?
- 3.2. Challenges
- 4.3. Features
- Corresponding English Capitalization (CAP):
- 5.2.2. Experiments
There exist two major challenges posed by focusing on Arabic NER: 1. Absence of capital letters in the orthography: English like many other Latin script based languages has a specific signal in the orthography, namely capitalization of the initial letter, indicating that a word or sequence of words is a named entity. Arabic has no such special sign...
The most challenging aspect of any machine learning approach to NLP problems is deciding on the optimal feature sets. In this work, we investigate a large space of features. The feature sets are characterized as follows. Contextual (CXT): This is an automatically generated feature that accounts for the different contexts in which NEs appear in the...
MADA provides the English translation for the words it morphologically disambiguates as a side effect of running the morphological disambiguation. In the process it taps into an underlying lexicon that provides bilingual information. The insight is that if the translation begins with a capital letter, then it is most probably a NE. This feature is ...
We have three sets of experiments in this paper: a baseline, a parameter setting set of experiments, and then feature engineering experiments.
Jan 1, 2022 · Unfortunately, named entity recognition is a difficult classification task to classify data into predefined labels, which is further challenged by the Arabic language's particular characteristics and complex nature.
Mar 22, 2021 · Named Entity Recognition (NER) is one of the fundamental tasks in Natural Language Processing (NLP), which aims to locate, extract, and classify named entities into a predefined category...
Named entity recognition (NER) is the task of identifying mentions that correspond to specific types, such as person name, location, and organization. Besides general domains, in several specific domains, such as the medical field, drugs, and clinical procedures can also be extracted by NER.
Named entity recognition (NER) is the task of identifying mentions that correspond to specific types, such as person name, location, and organization. Besides general domains, in several specific domains, such as the medical field, drugs, and clinical procedures can also be extracted by NER.
