Triple

T4378063
Position Surface form Disambiguated ID Type / Status
Subject Mikael E99056 entity
Predicate equivalentTo P6530 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: [Mikael, equivalentTo, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael
Context triple: [Mikael, equivalentTo, Michael]
  • A. Michael chosen
    Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
  • B. 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.
  • C. 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.
  • D. Michael Jackson
    Michael Jackson was an American singer, songwriter, and dancer known as the "King of Pop," celebrated for his groundbreaking music, iconic dance moves, and immense influence on popular culture.
  • E. King
    King is a prominent video game company best known for creating the massively popular mobile puzzle game Candy Crush Saga.
  • 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_69b3454ea8f48190a49c2436624d6ef6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35240092c81908e26ff607d665e7a completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e51907688190ad964d341eb84529 completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:18 p.m.