A knowledge graph (KG), a special form of semantic network, integrates fragmentary data
into a graph to support knowledge processing and reasoning. KG quality control is important …

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 …

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 …

Existing state of the art neural entity linking models employ attention-based bag-of-words
context model and pre-trained entity embeddings bootstrapped from word embeddings to …

In this paper, we introduce a new Multimodal Entity Linking (MEL) task on the multimodal
data. The MEL task discovers entities in multiple modalities and various forms within large …

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 …

Abstract Entity Linking (EL) empowers Natural Language Processing applications by linking
relevant mentions found in raw textual data to precise information about what they …

Entity linking (EL) for the rapidly growing short text (eg search queries and news titles) is
critical to industrial applications. Most existing approaches relying on adequate context for …

We present DeezyMatch, a free, open-source software library written in Python for fuzzy
string matching and candidate ranking. Its pair classifier supports various deep neural …

Digitization and digitalization efforts have led to an explosive growth of the number of
images that are published, shared, and made available in collections. In turn, this has …