Knowledge Tree
natural language querying
Also known as: natural language queries, natural language query, natural language searches
Facts (10)
Sources
LLM Knowledge Graph: Merging AI with Structured Data - PuppyGraph puppygraph.com Feb 19, 2026 2 facts
claimLLM knowledge graphs facilitate intuitive natural language querying by automatically translating natural language questions into formal graph queries, allowing users to access deep, relational data analysis without specialized query language skills.
accountWhen using the PuppyGraph RAG Chatbot, users can input natural language queries, such as requesting the five customer–product pairs with the largest total quantities ordered. The system allows users to verify the LLM's reasoning by expanding conversation details to view the generated formal query code, which demonstrates how the tool traverses graph relationships from customers through orders to products to aggregate and rank item quantities.
In the age of Industrial AI and knowledge graphs, don't overlook the ... symphonyai.com Aug 12, 2024 2 facts
claimUsers can utilize a generative AI copilot to search for actionable information in an industrial knowledge graph using natural language queries, such as "list all of the alerts for pumps in my area."
claimSymphonyAI combines role-based views with a generative AI copilot to allow users to perform natural language searches on industrial knowledge graphs.
KG-RAG: Bridging the Gap Between Knowledge and Creativity - arXiv arxiv.org May 20, 2024 2 facts
claimThe retrieval task in the KG-RAG framework is modeled as a search problem where the objective is to identify paths within a knowledge graph that connect relevant entities through relationships appropriate to a specific natural language query.
claimThe retrieval task in the KG-RAG framework is modeled as a search problem where the objective is to identify paths within a knowledge graph that connect relevant entities through relationships appropriate to a specific natural language query.
A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Nov 4, 2024 1 fact
claimLarge Language Models (LLMs) facilitate database management by translating complex natural language queries into structured query languages like SQL or graph query languages like GQL, allowing non-expert users to interact with databases more intuitively.
Unlocking the Potential of Generative AI through Neuro-Symbolic ... arxiv.org Feb 16, 2025 1 fact
referenceRajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay-Yoon Lee, Lizhen Tan, Lazaros Polymenakos, and Andrew McCallum authored 'Case-based reasoning for natural language queries over knowledge bases', published as an arXiv preprint (arXiv:2104.08762) in 2021.
Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org 1 fact
claimKnowledge graph question answering (KGQA) systems leverage natural language processing techniques to transform natural language queries into structured graph queries.
Large Language Models Meet Knowledge Graphs for Question ... arxiv.org Sep 22, 2025 1 fact
claimQuestion answering (QA) is a fundamental component in artificial intelligence, natural language processing, information retrieval, and data management, with applications including text generation, chatbots, dialog generation, web search, entity linking, natural language query, and fact-checking.