Genealogy AI Worked Example: [specific scenario]

 

1. Scenario: A concrete, historically plausible research situation with record type, time period, location, and research goal.
2. Research task: The exact action the genealogist should perform.
3. Exact prompt to use: A copy-ready AI prompt tailored to the scenario, including instructions to preserve uncertainty and avoid inventing facts.
4. Expected output structure: A compact outline or table schema the AI should return.
5. Verification warning: A clear caution explaining how to verify every extracted claim against the primary record image, citation, or original source before adding it to genealogy conclusions.
6. Quick morning note: Keep the full briefing short, practical, and easy to scan.

   Using AI with a probate packet

   Scenario

   You have a 40‑page probate packet (mixed wills, petitions, inventories, receipts) from a county‑level court, 1908, for “William H. Carter,” and you want:

7. A quick sense of whether this is “your” William
8. A structured list of people, relationships, and property
9. A timeline you can compare against other evidence

This pattern closely tracks how genealogists are already using AI for long legal files.[indigenousmexico]

---

Step 1 – Prepare the material

1. Scan or download the packet as images or PDF from the courthouse, FamilySearch, or another source.
2. If needed, use your preferred PDF splitter/combiner to break it into manageable chunks (e.g., 5–10 pages per upload).
3. Create a working transcript file where you’ll paste AI output and your corrections.

AI‑assisted summarization and extraction work best when the text is legible and chunked; this mirrors workflows described by working family historians.

---

Step 2 – Get a neutral summary of contents

Prompt to an AI tool (after you’ve supplied the text or images):

<prompt> 

Summarize this probate packet using only the text provided.
Identify:

• The deceased;
• All named heirs and their stated relationships;
• Executors/administrators, witnesses, and creditors;
• The main types of property and any described locations.
  Present the result as:

1. A short narrative summary;
2. A bullet list of key people;
3. A bullet list of properties.
   Do not infer relationships not explicitly stated. 

</prompt> 

This style of tight, “no‑inference” prompt reflects current best‑practice guidance for genealogists using AI to summarize legal records

You then:

• Compare the narrative against the images
• Mark any mis‑read names or places and correct them in your own transcript
• Note whether naming patterns match those expected for “your” William

---

Step 3 – Extract people, roles, and relationships into a table

Once you’ve corrected obvious OCR/reading errors, ask:

<prompt> 

“From the corrected text below, extract all personal names with their roles (decedent, heir, widow, child, creditor, witness, attorney, official, etc.), any explicitly stated relationships, and any dates and places connected to each person.
Present this as a table with columns: Name, Role, Relationship (as stated), Event/Context, Date (as stated), Place (as stated), Exact Wording.
Use only information actually present in the text and quote the wording that supports each entry.

</prompt> 

This mirrors extraction prompts recommended in current AI‑for‑genealogy guides.[indigenousmexico]

You now have:

• A person‑by‑event table you can paste into Airtable, a spreadsheet, or a Zotero note
• A quick way to see all heirs, children, and associates in one view
• Quotations you can treat as pointers back to the image for citation

---

Step 4 – Build a timeline and flag inconsistencies

Next, hand AI the same (or slightly cleaned) text and ask for a timeline:

<prompt>

Using only the text provided, build a chronological timeline of events in this probate file.
Include: event description, date (as written), place (as written), names involved, and the exact phrase supporting each entry.
Then list any internal inconsistencies you notice (e.g., conflicting dates, impossible ages, overlapping appointments).
Do not speculate beyond the wording.

</prompt> 

AI‑generated timelines with inconsistency checking are a widely recommended use in genealogical practice.

You then:

• Compare this timeline against your existing chronology for the known William H. Carter
• Highlight any conflicts (e.g., residence or occupation inconsistent with your candidate)
• Note additional locality clues (land descriptions, neighbors, named businesses)

---

Step 5 – Draft an evidence summary paragraph

Finally, use AI to help with structure, while you supply the reasoning:

<prompt >

“Using the table of people and the timeline above, draft a neutral evidence summary paragraph that describes what this probate file shows about the identity, family, residence, and property of William H. Carter.

Constraints:
Do not reach a conclusion about whether this is the same man as any other person; simply summarize what this file proves, distinguishing clearly between direct and indirect evidence.

Do not claim facts about real people unless supplied by the user or found in a cited primary source during the run. Emphasize evidence quality, source citation, and primary-record verification.

Do not speculate or invent anything. Use only the information I have provided.   

</prompt> 

This mirrors how genealogists are already using AI to speed up research‑report writing, while keeping conclusions in their own hands.[familyhistoryfanatics]

You then:

• Edit the paragraph to add citations and nuance
• Integrate it into a full research report or blog post
• Record in your log which AI tool you used, date, and what it did—matching current suggested practice.