Nested Named Entity Recognition Based on Dual Stream Feature Complementation
Entropy, 2022 Named entity recognition is a basic task in natural language processing, and there is a large number of nested structures in named entities. Nested named entities become the basis for solving many tasks in NLP.
Tao Liao +6 more
doaj +1 more source
Research Progress of Named Entity Recognition Based on Large Language Model [PDF]
Jisuanji kexue yu tansuoNamed entity recognition aims to identify named entities and their types from unstructured text, which is an important basic task in natural language processing technologies such as question answering system, machine translation and knowledge graph. With
LIANG Jia, ZHANG Liping, YAN Sheng, ZHAO Yubo, ZHANG Yawen
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An Approach for Chinese-Japanese Named Entity Equivalents Extraction Using Inductive Learning and Hanzi-Kanji Mapping Table [PDF]
, 2017 Named Entity Translation Equivalents extraction plays a critical role in machine translation (MT) and cross language information retrieval (CLIR). Traditional methods are often based on large-scale parallel or comparable corpora.
Araki, Kenji +4 more
core +1 more source
Word Embeddings for Entity-annotated Texts
, 2020 Learned vector representations of words are useful tools for many information retrieval and natural language processing tasks due to their ability to capture lexical semantics.
A Das +15 more
core +1 more source
An annotated corpus with nanomedicine and pharmacokinetic parameters [PDF]
, 2017 A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction
Jimenez, Ivan +2 more
core +2 more sources
Reassembling Fragmented Entity Names: A Novel Model for Chinese Compound Noun Processing
Electronics, 2023 In the process of classifying intelligent assets, we encountered challenges with a limited dataset dominated by complex compound noun phrases. Training classifiers directly on this dataset posed risks of overfitting and potential misinterpretations due to inherent ambiguities in these phrases.
Yuze Pan, Xiaofeng Fu
openaire +1 more source
NAMED ENTITY DISAMBIGUATION: A HYBRID APPROACH [PDF]
International Journal of Computational Intelligence Systems, 2012 Semantic annotation of named entities for enriching unstructured content is a critical step in development of Semantic Web and many Natural Language Processing applications.
HienT. Nguyen, TruH. Cao
doaj +1 more source
A Bidirectional Iterative Algorithm for Nested Named Entity Recognition
IEEE Access, 2020 Nested named entity recognition (NER) is a special case of structured prediction in which annotated sequences can be contained inside each other. It is a challenging and significant problem in natural language processing.
Slawomir Dadas, Jaroslaw Protasiewicz
doaj +1 more source
Concept Extraction Challenge: University of Twente at #MSM2013 [PDF]
, 2013 Twitter messages are a potentially rich source of continuously and instantly updated information. Shortness and informality of such messages are challenges for Natural Language Processing tasks. In this paper we present a hybrid approach for Named Entity
Habib, Mena B. +2 more
core +7 more sources
Establishing a New State-of-the-Art for French Named Entity Recognition [PDF]
, 2020 The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit information related to named entities, which are among the most useful information ...
Dupont, Yoann +4 more
core +2 more sources