Triple

T3764935
Position Surface form Disambiguated ID Type / Status
Subject Christopher Heyerdahl E82648 entity
Predicate notableWork P4 FINISHED
Object Tin Star E245036 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: Tin Star | Statement: [Christopher Heyerdahl, notableWork, Tin Star]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tin Star
Context triple: [Christopher Heyerdahl, notableWork, Tin Star]
  • A. Tin Star chosen
    Tin Star is a British-Canadian crime drama television series that follows a former London detective who becomes a small-town police chief in the Canadian Rockies, where his dark past and the town’s corruption collide.
  • B. The Tin Star
    The Tin Star is a 1947 short story by John W. Cunningham that provided the narrative basis for the classic Western film "High Noon."
  • C. Desert Star
    Desert Star is a crime novel by Michael Connelly featuring detective Harry Bosch working a cold case alongside LAPD detective Renée Ballard.
  • D. Dark Star
    "Dark Star" is an iconic, improvisation-heavy psychedelic rock song by the Grateful Dead that became a centerpiece of their live performances.
  • E. The Star
    The Star is a 1952 drama film starring Bette Davis as a fading Hollywood actress struggling with the loss of her fame and career.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbfd4be481908242c460a3f00c56 completed March 8, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5221ab08190a3599afbbd5dbc6e completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.