Machine knowledge: Creation and curation of comprehensive knowledge bases
Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
LearningToAdapt with word embeddings: Domain adaptation of Named Entity Recognition systems
Abstract The task of Named Entity Recognition (NER) is aimed at identifying named entities
in a given text and classifying them into pre-defined domain entity types such as persons …
in a given text and classifying them into pre-defined domain entity types such as persons …
Wiser: A semantic approach for expert finding in academia based on entity linking
We present Wiser, a new semantic search engine for expert finding in academia. Our system
is unsupervised and it jointly combines classical language modeling techniques, based on …
is unsupervised and it jointly combines classical language modeling techniques, based on …
KBPearl: a knowledge base population system supported by joint entity and relation linking
Nowadays, most openly available knowledge bases (KBs) are incomplete, since they are
not synchronized with the emerging facts happening in the real world. Therefore, knowledge …
not synchronized with the emerging facts happening in the real world. Therefore, knowledge …
[HTML][HTML] Leveraging Multi-source knowledge for Chinese clinical named entity recognition via relational graph convolutional network
Objective External knowledge, such as lexicon of words in Chinese and domain knowledge
graph (KG) of concepts, has been recently adopted to improve the performance of machine …
graph (KG) of concepts, has been recently adopted to improve the performance of machine …
[HTML][HTML] A discovery system for narrative query graphs: entity-interaction-aware document retrieval
Finding relevant publications in the scientific domain can be quite tedious: Accessing large-
scale document collections often means to formulate an initial keyword-based query …
scale document collections often means to formulate an initial keyword-based query …
Tree-KGQA: an unsupervised approach for question answering over knowledge graphs
Most Knowledge Graph-based Question Answering (KGQA) systems rely on training data to
reach their optimal performance. However, acquiring training data for supervised systems is …
reach their optimal performance. However, acquiring training data for supervised systems is …
PNEL: Pointer network based end-to-end entity linking over knowledge graphs
Question Answering systems are generally modelled as a pipeline consisting of a sequence
of steps. In such a pipeline, Entity Linking (EL) is often the first step. Several EL models first …
of steps. In such a pipeline, Entity Linking (EL) is often the first step. Several EL models first …
Narrative query graphs for entity-interaction-aware document retrieval
Finding relevant publications in the scientific domain can be quite tedious: Accessing large-
scale document collections often means to formulate an initial keyword-based query …
scale document collections often means to formulate an initial keyword-based query …
[HTML][HTML] CLART: A cascaded lattice-and-radical transformer network for Chinese medical named entity recognition
Chinese medical named entity recognition (NER) is a fundamental task in Chinese medical
natural language processing, aiming to recognize Chinese medical entities within …
natural language processing, aiming to recognize Chinese medical entities within …