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 …

Multi-modal named entity recognition (MNER) aims to discover named entities in free text
and classify them into pre-defined types with images. However, dominant MNER models do …

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 …

Multi-modal neural machine translation (NMT) aims to translate source sentences into a
target language paired with images. However, dominant multi-modal NMT models do not …

Entity Resolution (ER) links entities that refer to the same real-world entity from different
sources. Existing work usually takes pairs of entities as input and judges those pairs …

Incorporating lexicons into character-level Chinese NER by lattices is proven effective to
exploitrich word boundary information. Previous work has extended RNNs to consume …

More recently, Named Entity Recognition hasachieved great advances aided by pre-
trainingapproaches such as BERT. However, currentpre-training techniques focus on …

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" …

Integrating lexical knowledge in Chinese named entity recognition (NER) has been proven
effective. Among the existing methods, Flat-LAttice Transformer (FLAT) has achieved great …

Entity linking, bridging mentions in the contexts with their corresponding entities in the
knowledge bases, has attracted wide attention due to many potential applications. Recently …