Triple

T14806495
Position Surface form Disambiguated ID Type / Status
Subject Harry, He’s Here to Help E348050 entity
Predicate mainCharacter P1183 FINISHED
Object Michel E427344 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: Michel | Statement: [Harry, He’s Here to Help, mainCharacter, Michel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michel
Context triple: [Harry, He’s Here to Help, mainCharacter, Michel]
  • A. Michel
    Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
  • B. Michel chosen
    Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
  • C. Michel
    Michel is a French given name commonly used for males, equivalent to "Michael" in English.
  • D. Jean-Michel
    Jean-Michel is the given name of the influential American artist Jean-Michel Basquiat, a leading figure in 1980s neo-expressionist painting.
  • E. Jean-Michel
    Jean-Michel is the straight, headstrong son of Georges in the musical "La Cage aux Folles," whose engagement to a conservative politician’s daughter drives much of the show’s central conflict.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf33b6a08190ab6a4cfeda2cc09c completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dbced588190ab7712c7ad50ee67 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:40 a.m.