Knowledge Tree
Relations (1)
related 2.00 — strongly supporting 3 facts
Large Language Models are defined as probabilistic models of natural language [1] and are utilized to describe knowledge graph facts in natural language [2]. Furthermore, the inherent semantic gap between structured knowledge graphs and natural language is a central challenge in the effective reasoning of Large Language Models [3].
Facts (3)
Sources
Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org 1 fact
claimThe structured format of knowledge graphs often fails to capture the richness and flexibility of natural language, creating a semantic gap that leads to poor retrieval of relevant knowledge and ineffective reasoning by Large Language Models.
Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org 1 fact
claimLarge Language Models (LLMs) are probabilistic models of natural language that autoregressively estimate the likelihood of word sequences by analyzing text data.
A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com 1 fact
referenceIn LLM-augmented Knowledge Graphs, LLMs are used to improve KG representations, encode text or generate facts for KG completion, perform entity discovery and relation extraction for KG construction, describe KG facts in natural language, and connect natural language questions to KG-based answers, as cited in [55, 56, 57].