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The Cartographer
Leveraging small language models for Text2SPARQL tasks to improve the resilience of AI assistance
May 27, 2024 Β· Declared Dead Β· π D2R2
"No code URL or promise found in abstract"
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Authors
Felix Brei, Johannes Frey, Lars-Peter Meyer
arXiv ID
2405.17076
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CL,
cs.IR
Citations
18
Venue
D2R2
Last Checked
4 months ago
Abstract
In this work we will show that language models with less than one billion parameters can be used to translate natural language to SPARQL queries after fine-tuning. Using three different datasets ranging from academic to real world, we identify prerequisites that the training data must fulfill in order for the training to be successful. The goal is to empower users of semantic web technology to use AI assistance with affordable commodity hardware, making them more resilient against external factors.
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