Triple

T15475103
Position Surface form Disambiguated ID Type / Status
Subject Geoff Petrie E376763 entity
Predicate middleName P143 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: [Geoff Petrie, middleName, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael
Context triple: [Geoff Petrie, middleName, 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. Michael
    Michael is a central fictional character in the Australian television drama series "The Newsreader," which explores the personal and professional lives of journalists in the 1980s.
  • D. Michael
    Michael is a central figure in the crime drama "Sleepers," whose traumatic experiences and quest for justice drive much of the film’s emotional and moral conflict.
  • E. Mike
    Mike is the young boy protagonist of the 1992 family adventure film "Radio Flyer," which centers on his imaginative efforts to escape a troubled home life with his brother.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6e859481909c3d08343b7ad27c completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d093ccc8190aefc355a837c83f4 completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:34 a.m.