Constructing knowledge graphs (KGs) is essential for various natural language understanding tasks, such as question answering, information extraction, and recommendation systems. However, the process of building KGs is typically time-consuming and labor-intensive. This talk introduces technologies and tools to efficiently construct KGs using pre-trained language models (PLMs)
In recent decades, the amount of information that humankind has accumulated has increased tremendous...
Knowledge graphs have shown to be effective at capturing domain knowledge to extract value from data...
In today's world where data plays the very important role, we have various sources of pre-data like ...
Constructing knowledge graphs (KGs) is essential for various natural language understanding tasks, s...
Knowledge graphs (KGs) contain rich information about world knowledge, entities, and relations. Thus...
The use of knowledge graphs (KGs) enhances the accuracy and comprehensiveness of the responses provi...
In any system that uses structured knowledgegraph (KG) data as its underlying knowledge representati...
Knowledge-Enhanced Pre-trained Language Models (KEPLMs) are pre-trained models with relation triples...
Knowledge graph (KG) has been fully considered in natural language generation (NLG) tasks. A KG can ...
Pre-trained language representation models, such as BERT, capture a general language representation ...
In recent years, Knowledge Graph (KG) development has attracted significant researches considering t...
International audienceIn this article, we provide a comprehensive introduction to knowledge graphs, ...
The ability of knowledge graphs to represent complex relationships at scale has led to their adoptio...
International audienceWe propose the use of controlled natural language as a target for knowledge gr...
In this article, we provide a comprehensive introduction to knowledge graphs, which have recently ga...
In recent decades, the amount of information that humankind has accumulated has increased tremendous...
Knowledge graphs have shown to be effective at capturing domain knowledge to extract value from data...
In today's world where data plays the very important role, we have various sources of pre-data like ...
Constructing knowledge graphs (KGs) is essential for various natural language understanding tasks, s...
Knowledge graphs (KGs) contain rich information about world knowledge, entities, and relations. Thus...
The use of knowledge graphs (KGs) enhances the accuracy and comprehensiveness of the responses provi...
In any system that uses structured knowledgegraph (KG) data as its underlying knowledge representati...
Knowledge-Enhanced Pre-trained Language Models (KEPLMs) are pre-trained models with relation triples...
Knowledge graph (KG) has been fully considered in natural language generation (NLG) tasks. A KG can ...
Pre-trained language representation models, such as BERT, capture a general language representation ...
In recent years, Knowledge Graph (KG) development has attracted significant researches considering t...
International audienceIn this article, we provide a comprehensive introduction to knowledge graphs, ...
The ability of knowledge graphs to represent complex relationships at scale has led to their adoptio...
International audienceWe propose the use of controlled natural language as a target for knowledge gr...
In this article, we provide a comprehensive introduction to knowledge graphs, which have recently ga...
In recent decades, the amount of information that humankind has accumulated has increased tremendous...
Knowledge graphs have shown to be effective at capturing domain knowledge to extract value from data...
In today's world where data plays the very important role, we have various sources of pre-data like ...