Triple

T6489096
Position Surface form Disambiguated ID Type / Status
Subject Keystone Studios E147987 entity
Predicate employed P7 FINISHED
Object Hank Mann E150432 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: Hank Mann | Statement: [Keystone Studios, employed, Hank Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hank Mann
Context triple: [Keystone Studios, employed, Hank Mann]
  • A. Hank Mann chosen
    Hank Mann was a prolific silent film comedian and character actor, best known as one of the original Keystone Cops and for his numerous supporting roles in early Hollywood comedies.
  • B. William Parcher
    William Parcher is a mysterious, menacing government agent who appears as a figment of John Nash’s delusions in the film "A Beautiful Mind."
  • C. Jack Sullivan
    Jack Sullivan was a film industry professional recognized for his work in early Hollywood, notably earning the Academy Award for Best Assistant Director.
  • D. Leon Ames
    Leon Ames was an American character actor best known for his prolific film and television career from the 1930s through the 1970s, often portraying dignified fathers, professionals, and authority figures.
  • E. Major William Cage
    Major William Cage is the protagonist of the science fiction film "Edge of Tomorrow," a military public affairs officer who becomes caught in a time loop while fighting an alien invasion.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a97fff88190b6f993c14df62649 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653ba03288190ba4e4ce99d0ba32e completed March 27, 2026, 9:54 a.m.
Created at: March 22, 2026, 4:52 p.m.