Results 31 to 40 of about 408,758 (354)
Named Entity Recognition for Spoken Finnish [PDF]
Proceedings of the 2nd International Workshop on AI for Smart TV Content Production, Access and Delivery, 2020 In this paper we present a Bidirectional LSTM neural network with a Conditional Random Field layer on top, which utilizes word, character and morph embeddings in order to perform named entity recognition on various Finnish datasets. To overcome the lack of annotated training corpora that arises when dealing with low-resource languages like Finnish, we ...
Leinonen, Juho +3 more
openaire +4 more sources
Persian Named Entity Recognition [PDF]
2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 2017 Named Entity Recognition (NER) is an important natural language processing (NLP) tool for information extraction and retrieval from unstructured texts such as newspapers, blogs and emails. NER involves processing unstructured text for classification of words or expressions into relevant categories.
Dashtipour, Kia +5 more
openaire +2 more sources
A Survey on Deep Learning for Named Entity Recognition [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2018 Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc.
J. Li +3 more
semanticscholar +1 more source
BERN2: an advanced neural biomedical named entity recognition and normalization tool [PDF]
Bioinform., 2022 In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature.
Mujeen Sung +5 more
semanticscholar +1 more source
ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer
IEEE Access, 2023 Named Entity Recognition is an information extraction task that serves as a pre-processing step for other natural language processing tasks, such as machine translation, information retrieval, and question answering.
Ebrahim Chekol Jibril, A. Cuneyd Tantug
doaj +1 more source
Grounded Multimodal Named Entity Recognition on Social Media
Annual Meeting of the Association for Computational Linguistics, 2023 In recent years, Multimodal Named Entity Recognition (MNER) on social media has attracted considerable attention. However, existing MNER studies only extract entity-type pairs in text, which is useless for multimodal knowledge graph construction and ...
Jianfei Yu +3 more
semanticscholar +1 more source
T-NER: An All-Round Python Library for Transformer-based Named Entity Recognition [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2022 Language model (LM) pretraining has led to consistent improvements in many NLP downstream tasks, including named entity recognition (NER). In this paper, we present T-NER (Transformer-based Named Entity Recognition), a Python library for NER LM ...
Asahi Ushio, José Camacho-Collados
semanticscholar +1 more source
Named entity recognition method based on joint entity boundary detection
Journal of Hebei University of Science and Technology, 2023 To solve the problem that traditional named entity recognition methods cannot effectively utilize entity boundary information, a named entity recognition method based on joint entity boundary detection was proposed.
Xiaoteng LI, Zhinan GOU, Kai GAO
doaj +1 more source
Global Pointer: Novel Efficient Span-based Approach for Named Entity Recognition [PDF]
arXiv.org, 2022 Named entity recognition (NER) task aims at identifying entities from a piece of text that belong to predefined semantic types such as person, location, organization, etc.
Jianlin Su +7 more
semanticscholar +1 more source
Named Entity Extraction for Knowledge Graphs: A Literature Overview
IEEE Access, 2020 An enormous amount of digital information is expressed as natural-language (NL) text that is not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for representing information in computer-processable form. Natural Language
Tareq Al-Moslmi +3 more
doaj +1 more source