Triple

T3461996
Position Surface form Disambiguated ID Type / Status
Subject Mitch Williams E73045 entity
Predicate givenName P17 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: [Mitch Williams, givenName, Mitchell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell
Context triple: [Mitch Williams, 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. 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. Nate Mitchell
    Nate Mitchell is a technology entrepreneur best known as a co-founder of Oculus VR, a pioneering company in modern virtual reality hardware and software.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae867c4819091c76e63e44290b4 completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3611ff950819081b49f5c75aa6e4d completed March 13, 2026, 12:58 a.m.
Created at: March 8, 2026, 3:17 p.m.