Triple

T8802180
Position Surface form Disambiguated ID Type / Status
Subject Michael Wisdom E209436 entity
Predicate hasGivenName P17 FINISHED
Object Michael E21023 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 | Statement: [Michael Wisdom, hasGivenName, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael
Context triple: [Michael Wisdom, hasGivenName, Michael]
  • A. Michael chosen
    Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
  • B. Michael
    "Michael" is a 1996 fantasy-comedy film starring John Travolta as an unconventional archangel visiting Earth.
  • C. Kevin
    Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
  • D. Kevin
    Kevin is the young boy protagonist of the 1981 fantasy adventure film "Time Bandits," who joins a group of time-traveling dwarfs on a series of historical escapades.
  • E. Kevin
    Kevin is a character in the play "Clybourne Park," serving as one of the contemporary residents whose interactions highlight ongoing racial and social tensions in the gentrifying neighborhood.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fb9c5c88190881b069e1face10c completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f799f00819089159da177c816e9 completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:44 p.m.