Triple

T16780764
Position Surface form Disambiguated ID Type / Status
Subject Wonder Woman film series E407850 entity
Predicate featuresCharacter P626 FINISHED
Object Cheetah E730464 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: Cheetah | Statement: [Wonder Woman film series, featuresCharacter, Cheetah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheetah
Context triple: [Wonder Woman film series, featuresCharacter, Cheetah]
  • A. Cheetah
    Cheetah is the internal codename for Mac OS X 10.0, the first major release of Apple's Mac OS X operating system.
  • B. Cheetah chosen
    Cheetah is a classic DC Comics supervillain and archenemy of Wonder Woman, often depicted as a woman cursed or empowered with the speed, ferocity, and appearance of a cheetah.
  • C. Gepard
    The Gepard is a German self-propelled anti-aircraft gun system featuring twin 35 mm cannons and radar for tracking and engaging low-flying aircraft and drones.
  • D. Atlas Cheetah
    The Atlas Cheetah is a South African modernized variant of the Dassault Mirage III fighter aircraft, upgraded with advanced avionics and improved combat capabilities.
  • E. Gazelle
    The Gazelle is a light, fast, and highly maneuverable French-designed military helicopter widely used for reconnaissance, light attack, and training missions.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b214cebc81909de80e74b4bac5f8 completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab0300e48190ad088cd11098ca34 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:22 a.m.