Triple

T7358275
Position Surface form Disambiguated ID Type / Status
Subject His Airness E169681 entity
Predicate refersTo P37 FINISHED
Object Michael 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 Jordan | Statement: [His Airness, refersTo, Michael Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Jordan
Context triple: [His Airness, refersTo, Michael Jordan]
  • A. Michael Jordan
    Michael Jordan is a prominent computer scientist and statistician known for his influential work in machine learning, probabilistic graphical models, and statistical inference.
  • B. 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.
  • C. Michael Bakari Jordan
    Michael Bakari Jordan is an American actor and producer best known for his roles in films such as "Fruitvale Station," "Creed," and "Black Panther."
  • D. 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.
  • E. Kareem Abdul-Jabbar
    Kareem Abdul-Jabbar is a legendary American basketball center, the NBA’s all-time leading scorer for decades and a key figure in multiple championship teams, especially with the Los Angeles Lakers.
  • 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_69c68a59f2288190877ca15c19b1e822 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f13bf2e881909bc95b93a5664a4f completed March 27, 2026, 9:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c87067b98081908439af85623a97ea completed March 29, 2026, 12:20 a.m.
Created at: March 27, 2026, 3:06 p.m.