Named entity extraction for knowledge graphs: A literature overview
An enormous amount of digital information is expressed as natural-language (NL) text that is
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …
A contemporary review on utilizing semantic web technologies in healthcare, virtual communities, and ontology-based information processing systems
The semantic web is an emerging technology that helps to connect different users to create
their content and also facilitates the way of representing information in a manner that can be …
their content and also facilitates the way of representing information in a manner that can be …
Large-scale relation extraction from web documents and knowledge graphs with human-in-the-loop
Abstract The Semantic Web movement has produced a wealth of curated collections of
entities and facts, often referred as Knowledge Graphs. Creating and maintaining such …
entities and facts, often referred as Knowledge Graphs. Creating and maintaining such …
Onegen: Efficient one-pass unified generation and retrieval for llms
Despite the recent advancements in Large Language Models (LLMs), which have
significantly enhanced the generative capabilities for various NLP tasks, LLMs still face …
significantly enhanced the generative capabilities for various NLP tasks, LLMs still face …
Knowledge Graphs for Enhancing Large Language Models in Entity Disambiguation
Abstract Recent advances in Large Language Models (LLMs) have positioned them as a
prominent solution for Natural Language Processing tasks. Notably, they can approach …
prominent solution for Natural Language Processing tasks. Notably, they can approach …
Mining and leveraging background knowledge for improving named entity linking
Knowledge-rich Information Extraction (IE) methods aspire towards combining classical IE
with background knowledge obtained from third-party resources. Linked Open Data …
with background knowledge obtained from third-party resources. Linked Open Data …
Collective disambiguation in entity linking based on topic coherence in semantic graphs
Entity Linking (EL) consists of determinating the entities that best represent the mentions in a
document. Mentions can be very ambiguous and can refer to different entities in different …
document. Mentions can be very ambiguous and can refer to different entities in different …
EntGPT: Linking Generative Large Language Models with Knowledge Bases
The ability of Large Language Models (LLMs) to generate factually correct output remains
relatively unexplored due to the lack of fact-checking and knowledge grounding during …
relatively unexplored due to the lack of fact-checking and knowledge grounding during …
ChatEL: Entity Linking with Chatbots
Entity Linking (EL) is an essential and challenging task in natural language processing that
seeks to link some text representing an entity within a document or sentence with its …
seeks to link some text representing an entity within a document or sentence with its …
WikiGUM: Exhaustive entity linking for Wikification in 12 genres
Previous work on Entity Linking has focused on resources targeting non-nested proper
named entity mentions, often in data from Wikipedia, ie Wikification. In this paper, we present …
named entity mentions, often in data from Wikipedia, ie Wikification. In this paper, we present …