Summary of Integrating Large Language Models and Knowledge Graphs For Extraction and Validation Of Textual Test Data, by Antonio De Santis et al.
Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data
by Antonio De Santis, Marco Balduini, Federico De Santis, Andrea Proia, Arsenio Leo, Marco Brambilla, Emanuele Della Valle
First submitted to arxiv on: 3 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 This paper proposes a hybrid methodology that combines Knowledge Graphs (KGs) and Large Language Models (LLMs) to extract and validate data from unstructured documents in aerospace manufacturing. The approach is applied to test data related to electronic boards for satellites, leveraging the Semantic Sensor Network ontology. By storing metadata in a KG and actual test results in parquet, accessible via a Virtual Knowledge Graph, the validation process can be managed using an LLM-based approach. A benchmarking study evaluates the performance of state-of-the-art LLMs in executing this task, highlighting the costs and benefits of automating manual data extraction and validation processes for subsequent cross-report analyses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps companies like Thales Alenia Space make sense of lots of complex and hard-to-analyze documents. They want to find specific information across many documents quickly and accurately. The researchers come up with a new way to use special computer programs called Knowledge Graphs and Large Language Models to do this. It’s tested on data about satellite electronics, which is very helpful for companies that make satellites. This new method can help automate tasks that are currently done manually, saving time and money. |
Keywords
» Artificial intelligence » Knowledge graph
