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 …

The rapid development of data and artificial intelligence technology has introduced new
opportunities and challenges to aeronautical information intelligence. However, there are …

Natural language understanding (NLU) in the context of goal-oriented dialog systems
typically includes intent classification and slot labeling tasks. Existing methods to expand an …

Abstract Named Entity Recognition (NER) for low-resource languages is a both practical and
challenging research problem. This paper addresses zero-shot transfer for cross-lingual …

We study the selection of transfer languages for different Natural Language Processing
tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In …

Machine Translation (MT) has been widely used for cross-lingual classification, either by
translating the test set into English and running inference with a monolingual model …

We present WojoodNER-2024, the second Arabic Named Entity Recognition (NER) Shared
Task. In WojoodNER-2024, we focus on fine-grained Arabic NER. We provided participants …

Traditional NER systems are typically trained to recognize coarse-grained entities, and less
attention is given to classifying entities into a hierarchy of fine-grained lower-level subtypes …

In cross-lingual named entity recognition (NER), self-training is commonly used to bridge the
linguistic gap by training on pseudo-labeled target-language data. However, due to sub …

We present, Naamapadam, the largest publicly available Named Entity Recognition (NER)
dataset for the 11 major Indian languages from two language families. The dataset contains …