Triple

T1477690
Position Surface form Disambiguated ID Type / Status
Subject Michael Jordan E30880 entity
Predicate fullName P16 FINISHED
Object Michael Jeffrey Jordan E30880 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: Michael Jeffrey Jordan | Statement: [Michael Jordan, fullName, Michael Jeffrey Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Jeffrey Jordan
Context triple: [Michael Jordan, fullName, Michael Jeffrey Jordan]
  • A. Michael Jordan chosen
    Michael Jordan is a legendary American basketball player widely regarded as one of the greatest athletes in the history of the sport.
  • B. Kobe Bryant
    Kobe Bryant was an American professional basketball player, primarily with the Los Angeles Lakers, widely regarded as one of the greatest players in NBA history.
  • C. George Gervin
    George Gervin is a Hall of Fame American basketball player, nicknamed "The Iceman," renowned as one of the greatest scorers in ABA and NBA history.
  • D. Maye
    Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
  • E. Earvin
    Earvin is the given first name of Magic Johnson, the legendary American basketball player and NBA Hall of Famer.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c605d4c0819088ab06678b2ba6f3 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15add78c8190843efd75bbe8423f completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8:11 p.m.