Pythia: Facilitating Access to Internet Data Using LLMs and IYP

Internet data analysis is essential for policymakers and regulators to make informed decisions. Despite the various datasets made available by the research community, the analysis of these datasets is challenging due to their various formats and required analysis tools. The Internet Yellow Pages (IYP) database is designed to simplify Internet data analysis by combining many datasets into a single format. Hence, IYP enables users to retrieve data from various Internet datasets using a single querying language called Cypher. However, learning Cypher and understanding IYP’s schema is still challenging. Large Language Models (LLMs) offer the potential to generate Cypher queries from English text. In this paper, we assess the ability of different LLMs to generate Cypher queries. We introduce CypherEval, a dataset for evaluating LLM-generated Cypher queries, and we propose a methodology to benchmark LLMs for IYP. Finally, we present Pythia, a system for the generation of IYP Cypher queries.

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Publication Details

Published
2025-09-15
DOI
https://doi.org/10.1109/lcn65610.2025.11146364
Primary Topic
Digital Rights Management and Security
Type
article
Field-Weighted Citation Impact
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article

Pythia: Facilitating Access to Internet Data Using LLMs and IYP

Malte Tashiro, Romain Fontugne, Dimitrios Panteleimon Giakatos
Digital Rights Management and Security
article

Pythia: Facilitating Access to Internet Data Using LLMs and IYP

Malte Tashiro, Romain Fontugne, Dimitrios Panteleimon Giakatos
article en

Abstract

Internet data analysis is essential for policymakers and regulators to make informed decisions. Despite the various datasets made available by the research community, the analysis of these datasets is challenging due to their various formats and required analysis tools. The Internet Yellow Pages (IYP) database is designed to simplify Internet data analysis by combining many datasets into a single format. Hence, IYP enables users to retrieve data from various Internet datasets using a single querying language called Cypher. However, learning Cypher and understanding IYP’s schema is still challenging. Large Language Models (LLMs) offer the potential to generate Cypher queries from English text. In this paper, we assess the ability of different LLMs to generate Cypher queries. We introduce CypherEval, a dataset for evaluating LLM-generated Cypher queries, and we propose a methodology to benchmark LLMs for IYP. Finally, we present Pythia, a system for the generation of IYP Cypher queries.

IIJ Research Laboratory (JP)
Openalex Percentile: Top 64%
Digital Rights Management and Security
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Pythia: Facilitating Access to Internet Data Using LLMs and IYP — Malte Tashiro, Romain Fontugne, et al. · (2025) | TGRS Research Map | TGRS