Triple

T4333231
Position Surface form Disambiguated ID Type / Status
Subject John Hay E97401 entity
Predicate spouse P13 FINISHED
Object Clara Louise Stone
Clara Louise Stone was the wife of American statesman and author John Hay, noted for her role in Washington, D.C. social circles during his diplomatic and political career.
 E432908 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Clara Louise Stone | Statement: [John Hay, spouse, Clara Louise Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Clara Louise Stone
Context triple: [John Hay, spouse, Clara Louise Stone]
  • A. Sarah Lucille Stone
    Sarah Lucille Stone was the wife of prominent American architect Edward Durell Stone.
  • B. Clara Bingham
    Clara Bingham is an American journalist, author, and documentary producer known for her investigative work on gender, power, and workplace harassment.
  • C. Clara Clayton
    Clara Clayton is a schoolteacher from the Old West and Doc Brown’s love interest in the film "Back to the Future Part III."
  • D. Clara Hesperia Bannister Congdon
    Clara Hesperia Bannister Congdon was a prominent early 20th-century Duluth, Minnesota philanthropist and matriarch of the influential Congdon family.
  • E. Allene Stone Gano
    Allene Stone Gano was the mother of American business magnate and aviator Howard Hughes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Clara Louise Stone
Triple: [John Hay, spouse, Clara Louise Stone]
Generated description
Clara Louise Stone was the wife of American statesman and author John Hay, noted for her role in Washington, D.C. social circles during his diplomatic and political career.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Clara Louise Stone
Target entity description: Clara Louise Stone was the wife of American statesman and author John Hay, noted for her role in Washington, D.C. social circles during his diplomatic and political career.
  • A. Sarah Lucille Stone
    Sarah Lucille Stone was the wife of prominent American architect Edward Durell Stone.
  • B. Clara Bingham
    Clara Bingham is an American journalist, author, and documentary producer known for her investigative work on gender, power, and workplace harassment.
  • C. Clara Clayton
    Clara Clayton is a schoolteacher from the Old West and Doc Brown’s love interest in the film "Back to the Future Part III."
  • D. Clara Hesperia Bannister Congdon
    Clara Hesperia Bannister Congdon was a prominent early 20th-century Duluth, Minnesota philanthropist and matriarch of the influential Congdon family.
  • E. Allene Stone Gano
    Allene Stone Gano was the mother of American business magnate and aviator Howard Hughes.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3514faaac819081475681fd10da24 completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db9c1a90819083d0889a65f04af2 completed March 14, 2026, 10:05 p.m.
NEDg Description generation batch_69b5dc7763488190b056ba759ac9fa73 completed March 14, 2026, 10:08 p.m.
NED2 Entity disambiguation (via description) batch_69b5dd07854c8190ac55586d245028a6 completed March 14, 2026, 10:11 p.m.
Created at: March 12, 2026, 11:13 p.m.