Triple

T17839478
Position Surface form Disambiguated ID Type / Status
Subject Puma helicopter E445483 entity
Predicate hasTakeoffAndLandingCapability P129376 FINISHED
Object vertical takeoff and landing LITERAL 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: vertical takeoff and landing | Statement: [Puma helicopter, hasTakeoffAndLandingCapability, vertical takeoff and landing]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTakeoffAndLandingCapability
Context triple: [Puma helicopter, hasTakeoffAndLandingCapability, vertical takeoff and landing]
  • A. shortTakeoffAndLandingCapability
    Indicates that an entity has the ability to take off and land safely on runways or surfaces that are significantly shorter than standard operational requirements.
  • B. landingCapability
    Indicates the ability or suitability of an entity (e.g., a vehicle or system) to perform a landing under specified conditions.
  • C. hasLandingCharacteristics
    Indicates that an entity possesses specific attributes or features related to how it lands or is capable of landing.
  • D. hasLandingSystem
    Indicates that an entity is equipped with or utilizes a particular landing system for performing landings.
  • E. landingGearType
    Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
  • F. None of above. chosen

Provenance (4 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2a570c81909787296bde7e795c completed April 19, 2026, 8:07 a.m.
PD Predicate disambiguation batch_69e3d8e266888190ae976b4b7d5b886f completed April 18, 2026, 7:17 p.m.
PDg Predicate description generation batch_69e3f022ec448190a9bf191be1c5f570 completed April 18, 2026, 8:57 p.m.
Created at: April 10, 2026, 10:16 a.m.