Triple

T15437178
Position Surface form Disambiguated ID Type / Status
Subject In the Gloaming E369794 entity
Predicate productionCompany P490 FINISHED
Object HBO Pictures E1085183 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: HBO Pictures | Statement: [In the Gloaming, productionCompany, HBO Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HBO Pictures
Context triple: [In the Gloaming, productionCompany, HBO Pictures]
  • A. HBO Pictures chosen
    HBO Pictures was the original feature film production arm of the HBO cable network, known for producing made-for-television movies and miniseries.
  • B. Benaroya Pictures
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful feature films.
  • C. Magnolia Pictures
    Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
  • D. Empire Pictures
    Empire Pictures was an independent American film production and distribution company best known for low-budget horror, fantasy, and science fiction movies in the 1980s.
  • E. Sycamore Pictures
    Sycamore Pictures is an American film production company known for financing and producing independent and mid-budget feature films.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edca064819081510bf303271062 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a7d44481909a26b5cc331a3259 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:21 a.m.