Summary of Linkq: An Llm-assisted Visual Interface For Knowledge Graph Question-answering, by Harry Li et al.
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering
by Harry Li, Gabriel Appleby, Ashley Suh
First submitted to arxiv on: 7 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary LinkQ is a system that uses a large language model to help users construct knowledge graph queries through natural language question-answering. Traditional approaches require expertise in graph querying languages, limiting access to valuable insights from KGs. LinkQ simplifies this process by converting user questions into well-formed queries through a multistep protocol, supporting targeted and exploratory analysis. The system guards against LLM hallucinations by ensuring only ground truth KG data is used for answers. We demonstrate the efficacy of LinkQ with a qualitative study involving five KG practitioners, who find it effective for KG question-answering and desire future systems for exploratory data analysis. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary LinkQ helps people ask good questions about knowledge graphs. Right now, asking questions about these complex databases can be tricky because you need to know special languages like SPARQL or Cypher. LinkQ makes this easier by using a super smart language model that understands what you’re asking and turns it into the right query. This means you can get answers from your knowledge graph without needing to be an expert in querying languages. We showed five experts how well LinkQ works, and they liked it so much that they want more tools like this for exploring data. |
Keywords
» Artificial intelligence » Knowledge graph » Language model » Large language model » Question answering
