It has been shown that named entity recognition (NER) could benefit from incorporating the
long-distance structured information captured by dependency trees. However, dependency …

It has been shown that named entity recognition (NER) could benefit from incorporating the
long-distance structured information captured by dependency trees. We believe this is …

In this paper we investigate the role of the dependency tree in a named entity recognizer
upon using a set of GCN. We perform a comparison among different NER architectures and …

Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic
properties where entities may be extracted according to how they are used and placed in the …

In natural language processing, it is common that many entities contain other entities inside
them. Most existing works on named entity recognition (NER) only deal with flat entities but …

Abstract Named Entity Recognition (NER) is fundamental in natural language processing,
involving identifying entity spans and types within a sentence. Nested NER contains other …

Named entity recognition (NER) isa preliminary task in natural language processing (NLP).
Recognizing Chinese named entities from unstructured texts is challenging due to the lack …

The dominant approaches for named entity recognitionm (NER) mostly adopt complex
recurrent neural networks (RNN), eg, long-short-term-memory (LSTM). However, RNNs are …

Named entity recognition is one of the core tasks in NLP. Although many improvements
have been made on this task during the last years, the state-of-the-art systems do not …

Abstract Nested Named Entity Recognition (NNER) has been extensively studied, aiming to
identify all nested entities from potential spans (ie, one or more continuous tokens) …