I am building a map of people who lived in the Roman Empire

Driving home from work one day, I wanted to know how many people we knew the names of who lived during the Roman era. Searching around, I found lists of Consuls and officials, but nothing that covered ordinary people or even most people like freedmen and slaves. So I ended up building a pipeline to process the more than 500k Latin inscriptions in the Epigraphic Database Clauss-Slaby https://edcs.hist.uzh.ch/en/ and extract the names of people (and attempt to cluster them, but this is a work in progress).There are databases where Classicists have done this manually for specific regions, Trismegistos https://www.trismegistos.org/ and Latin Inscriptions of the Roman Empire (LIRE) https://pure.au.dk/portal/en/publications/latin-inscriptions... are two major efforts I found. But there doesn't seem to be a project that did what I set out to do, although I have read in some places that it was believed to be possible.I am not a classicist or a web developer, but I have Claude and Gemini and I can sort of read basic Latin - so I set to work. I used LIRE and another database as ground truth and built a pipeline to extract and process the inscriptions to recover the names. The process I developed uses a high end LLM like Sonnet or Gemini Pro to supervise the extraction and tuning process on a regional basis until the obvious error rate is reasonable. For this, so far, reasonable to me means less than 1-2% in the smaller initial samples of 100-500 and no observed systemic issues. The different regions often need different prompts, so this basically became an exercise in letting the higher level AI tune the prompt for the lower level AI. The extraction when measured against LIRE produces an F1 score between 0.64 and 0.87, but take this with a grain of salt.Once I had done a few regions, I wanted to see the work, so I threw together a pretty crude website but as I am not a web developer, it was crude in how it

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FL score

62

out of 100

Verdict

VALIDATE

medium confidence

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An LLM-powered extraction tool that converts 500k Latin inscriptions into a searchable database of Roman Empire inhabitants, filling a gap between specialized regional databases and comprehensive coverage.

The pain

Classicists and historians cannot easily search across all known names of ordinary Romans (non-elites, freedmen, slaves). Existing databases like Trismegistos cover specific regions manually. The comprehensive picture of who actually lived in the Roman Empire remains fragmented and inaccessible.

The gap

No single, machine-processed database exists that covers the full Clauss-Slaby corpus of 500k inscriptions with reasonable accuracy. The manual approach doesn't scale. The automated approach hasn't been attempted at this scope before.

Build angle

Continue building the extraction pipeline with rigorous validation against LIRE and Trismegistos. Focus on: (1) improving F1 scores above 0.85 across all regions, (2) solving the name-clustering problem to deduplicate individuals, (3) creating a usable interface for academic researchers to query and contribute corrections. Position as infrastructure for digital humanities rather than a consumer product.

Strengths

  • Solves a real, specific problem that existing tools don't address at scale
  • Clear ground truth available (LIRE, Trismegistos) for validation
  • Technical approach is sound, using LLMs to supervise extraction is practical and reproducible
  • Builder has already done the hard work of processing multiple regions and validating results
  • Natural academic audience with clear use cases (prosopography, demographic studies, social network analysis)

Risks

  • F1 scores of 0.64-0.87 mean 13-36% of extracted names are wrong or missed, acceptable for exploration but not for publication without major improvement
  • Name clustering is unsolved and critical; without it, the database conflates different people with the same name
  • Market is small: academic historians and classicists. Monetization is unclear. Funding likely requires grants or institutional partnerships
  • Builder is not a classicist, so domain credibility matters for adoption. Errors could damage reputation with the target audience
  • Crude website suggests execution risk. Academic tools require documentation, API access, and integration with existing workflows (not just a map view)
  • Competing projects (Trismegistos, LIRE) are already trusted by the field. Adoption requires demonstrable advantages, not just coverage

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