Triple

T8082567
Position Surface form Disambiguated ID Type / Status
Subject William D. Mitchell E188652 entity
Predicate familyName P18 FINISHED
Object Mitchell E81076 NE FINISHED

How this triple was built (2 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: Mitchell | Statement: [William D. Mitchell, familyName, Mitchell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell
Context triple: [William D. Mitchell, familyName, Mitchell]
  • A. Mitchell
    Mitchell is a small rural town in Queensland, Australia, known as a service centre for the surrounding agricultural region and for its artesian spa and historic outback character.
  • B. Mitchell
    Mitchell Kapor is an American entrepreneur and software designer best known for founding Lotus Development Corporation and co-creating the Lotus 1-2-3 spreadsheet program.
  • C. Mitchell chosen
    Mitchell is a common English-language surname of Scottish and English origin, borne by numerous notable individuals across fields such as politics, sports, and the arts.
  • D. Mitchell
    Mitchell is a small city in western Nebraska, United States, known for its agricultural surroundings and proximity to the Scotts Bluff National Monument.
  • E. Mitchell Ryan
    Mitchell Ryan was an American character actor known for his tough, authoritative roles in film and television, including notable appearances in projects like Magnum Force and Lethal Weapon.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb415cb4688190920868317e77bbff completed March 31, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63fba1148190b8d0f04faa5330a1 completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:28 p.m.