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Entity linking meets deep learning: Techniques and solutions
Entity linking (EL) is the process of linking entity mentions appearing in web text with their
corresponding entities in a knowledge base. EL plays an important role in the fields of …
corresponding entities in a knowledge base. EL plays an important role in the fields of …
Neural entity linking: A survey of models based on deep learning
This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …
systems developed since 2015 as a result of the “deep learning revolution” in natural …
Entity linking via joint encoding of types, descriptions, and context
For accurate entity linking, we need to capture various information aspects of an entity, such
as its description in a KB, contexts in which it is mentioned, and structured knowledge …
as its description in a KB, contexts in which it is mentioned, and structured knowledge …
Neural collective entity linking
Joint entity linking with deep reinforcement learning
Entity linking is the task of aligning mentions to corresponding entities in a given knowledge
base. Previous studies have highlighted the necessity for entity linking systems to capture …
base. Previous studies have highlighted the necessity for entity linking systems to capture …
A survey on multimodal knowledge graphs: Construction, completion and applications
Y Chen, X Ge, S Yang, L Hu, J Li, J Zhang - Mathematics, 2023 - mdpi.com
As an essential part of artificial intelligence, a knowledge graph describes the real-world
entities, concepts and their various semantic relationships in a structured way and has been …
entities, concepts and their various semantic relationships in a structured way and has been …
Learning dynamic context augmentation for global entity linking
Despite of the recent success of collective entity linking (EL) methods, these" global"
inference methods may yield sub-optimal results when the" all-mention coherence" …
inference methods may yield sub-optimal results when the" all-mention coherence" …
Bridge text and knowledge by learning multi-prototype entity mention embedding
Integrating text and knowledge into a unified semantic space has attracted significant
research interests recently. However, the ambiguity in the common space remains a …
research interests recently. However, the ambiguity in the common space remains a …
A contrastive learning framework for event detection via semantic type prototype representation modelling
The diversity of natural language expressions for describing events poses a challenge for
the task of Event Detection (ED) with machine learning methods. To detect and classify …
the task of Event Detection (ED) with machine learning methods. To detect and classify …