Triple

T20744539
Position Surface form Disambiguated ID Type / Status
Subject CinemaNX E510542 entity
Predicate notableWork P4 FINISHED
Object Triangle NE NERFINISHED

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: Triangle | Statement: [CinemaNX, notableWork, Triangle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Triangle
Context triple: [CinemaNX, notableWork, Triangle]
  • A. Triangle
    Triangle is a small sugar-producing town in southeastern Zimbabwe known for its large sugar estates and milling operations.
  • B. Triangle chosen
    "Triangle" is a 2009 psychological horror-thriller film known for its mind-bending time-loop narrative and unsettling atmosphere.
  • C. Triangle
    Triangle is a British television drama series, best known for its stories set aboard a North Sea ferry and for featuring actress Kate O'Mara.
  • D. Triangles
    "Triangles" is a notable photographic work by American photographer Imogen Cunningham, exemplifying her modernist approach and emphasis on abstract geometric forms.
  • E. Trianguli
    Trianguli is the Latin genitive form of Triangulum, the name of a small constellation in the northern sky.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c21197088190951a4c4a7e765891 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.