Triple

T1862450
Position Surface form Disambiguated ID Type / Status
Subject Mitchell Kapor E34845 entity
Predicate givenName P17 FINISHED
Object Mitchell E30388 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: [Mitchell Kapor, givenName, Mitchell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell
Context triple: [Mitchell Kapor, givenName, Mitchell]
  • A. Mitchell chosen
    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.
  • B. Mitchell
    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.
  • C. Doug Mitchell
    Doug Mitchell is an Australian film producer best known for his longtime collaboration with director George Miller on projects including the Mad Max franchise.
  • D. Myles
    Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
  • E. Hayes
    Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb09e714881909cef0f7e77b5b3b9 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf4ecdc08190a264b358d3883f70 completed March 8, 2026, 8:42 p.m.
Created at: March 4, 2026, 7:34 p.m.