Triple

T16580470
Position Surface form Disambiguated ID Type / Status
Subject Cheat E402813 entity
Predicate productionCompany P490 FINISHED
Object Two Brothers Pictures E970828 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: Two Brothers Pictures | Statement: [Cheat, productionCompany, Two Brothers Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Two Brothers Pictures
Context triple: [Cheat, productionCompany, Two Brothers Pictures]
  • A. Two Brothers Pictures chosen
    Two Brothers Pictures is a British television production company known for creating acclaimed drama series such as "Fleabag" and "The Missing."
  • B. Sister Pictures
    Sister Pictures is a British television production company known for creating high-profile, critically acclaimed drama series.
  • C. 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.
  • D. Troika Pictures
    Troika Pictures is a film production company known for producing feature films such as the thriller "The Call" (2013).
  • E. Dimension Pictures
    Dimension Pictures was an American independent film production and distribution company known for releasing low-budget exploitation and genre films in the 1970s.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35960834c819080eed0c9f32b881d completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ef0bc4c8190b06b03c06d344abf completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.