Triple

T10390706
Position Surface form Disambiguated ID Type / Status
Subject The Gray Man E244884 entity
Predicate producer P490 FINISHED
Object Mike Larocca E486292 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: Mike Larocca | Statement: [The Gray Man, producer, Mike Larocca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Larocca
Context triple: [The Gray Man, producer, Mike Larocca]
  • A. Mike Larocca chosen
    Mike Larocca is a film producer known for his work on acclaimed projects including the multiverse-themed movie "Everything Everywhere All at Once."
  • B. Mike Piscitelli
    Mike Piscitelli is a filmmaker and photographer known for his music videos, commercials, and visual collaborations with various artists.
  • C. Phil Sgriccia
    Phil Sgriccia is an American television producer and director best known for his extensive work on genre series such as Supernatural and The Boys.
  • D. Greg Corrado
    Greg Corrado is an American computer scientist and researcher known for his pioneering work in artificial intelligence and deep learning, including co-founding Google Brain.
  • E. Anthony DeLuca
    Anthony DeLuca is a character from the 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls and their manager.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b4f7d08190bcb16d3b4c8f22ad completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e5561714a081909cbf1cc7d5d0ac0a completed April 19, 2026, 10:24 p.m.
Created at: April 6, 2026, 12:06 p.m.