Triple

T21115528
Position Surface form Disambiguated ID Type / Status
Subject Mitchell Kennerley E520287 entity
Predicate givenName P17 FINISHED
Object Mitchell NE NERFINISHED

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 Kennerley, givenName, Mitchell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell
Context triple: [Mitchell Kennerley, givenName, Mitchell]
  • A. 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.
  • B. 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.
  • C. 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.
  • 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
    Mitchell is a 1975 American action-crime film starring Joe Don Baker as a tough, unorthodox police detective.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72105bd648190beecc636284397bd completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.