Results 21 to 30 of about 14,087 (197)
An Entity Disambiguation Method Based on Deep Learning
Nantong Daxue xuebao. Ziran kexue ban, 2021 The traditional named entity disambiguation technology usually relies on rich context and knowledge of external entities. However, many emerging entities lack knowledge bases and the text containing entities is short.
WEN Wanzhi; JIANG Wenxuan; GE Wei; ZHU Kai; LI Xikai; WU Xuefei
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Named Entity Disambiguation for Maritime-related Data Retrieved from Heterogenous Sources [PDF]
TransNav, 2016 The article concerns integration and disambiguation of data related to the maritime domain. A developed system is described, which collects and merges data about several maritime-related entities (vessels, vessel types, ports, companies etc.) retrieved ...
Jacek Malyszko +2 more
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Cluster-based mention typing for named entity disambiguation [PDF]
Natural Language Engineering, 2020 AbstractAn entity mention in text such as “Washington” may correspond to many different named entities such as the city “Washington D.C.” or the newspaper “Washington Post.” The goal of named entity disambiguation (NED) is to identify the mentioned named entity correctly among all possible candidates.
Çelebi, Arda, Özgür, Arzucan
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ISPRS International Journal of Geo-Information, 2021 Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recognized
Zheren Yan +5 more
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MLNet: a multi-level multimodal named entity recognition architecture
Frontiers in Neurorobotics, 2023 In the field of human–computer interaction, accurate identification of talking objects can help robots to accomplish subsequent tasks such as decision-making or recommendation; therefore, object determination is of great interest as a pre-requisite task.
Hanming Zhai +4 more
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Adapting vs. Pre-training Language Models for Historical Languages [PDF]
Journal of Data Mining and Digital Humanities, 2022 As large language models such as BERT are becoming increasingly popular in Digital Humanities (DH), the question has arisen as to how such models can be made suitable for application to specific textual domains, including that of 'historical text'. Large
Enrique Manjavacas, Lauren Fonteyn
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Neural Network-Based Tree Translation for Knowledge Base Construction
IEEE Access, 2021 Knowledge bases (KB), such as Probase and ConceptNet, play an important role in many natural language processing tasks. Compared with resource-poor languages such as Chinese, the scale and quality of English knowledge bases are obviously superior.
Haijun Zhang
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Candidate entity generation in lexical semantics [PDF]
PeerJ Computer ScienceCandidate entity generation plays a pivotal role in various Natural Language Processing tasks, particularly in lexical semantics, where identifying and selecting relevant entities is crucial for effective understanding and processing of text.
Madawi Saqer Alotaibi +1 more
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Enhancement of Question Answering System Accuracy via Transfer Learning and BERT
Applied Sciences, 2022 Entity linking and predicate matching are two core tasks in the Chinese Knowledge Base Question Answering (CKBQA). Compared with the English entity linking task, the Chinese entity linking is extremely complicated, making accurate Chinese entity linking ...
Kai Duan +5 more
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DoSeR - A Knowledge-Base-Agnostic Framework for Entity Disambiguation Using Semantic Embeddings [PDF]
, 2016 Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entities in a knowledge base. It finds its application in the extraction of structured data in RDF (Resource Description Framework) from textual documents, but ...
Granitzer, Michael +2 more
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