Triple

T33038909
Position Surface form Disambiguated ID Type / Status
Subject Learjet 70 E845399 entity
Predicate avionicsModel P7133 FINISHED
Object Garmin G5000
The Garmin G5000 is an advanced integrated flight deck system featuring large-format touchscreen displays, synthetic vision, and sophisticated navigation and automation capabilities for modern business and regional aircraft.
 E2034046 NE FINISHED

How this triple was built (3 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: Garmin G5000 | Statement: [Learjet 70, avionicsModel, Garmin G5000]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Garmin G5000
Triple: [Learjet 70, avionicsModel, Garmin G5000]
Generated description
The Garmin G5000 is an advanced integrated flight deck system featuring large-format touchscreen displays, synthetic vision, and sophisticated navigation and automation capabilities for modern business and regional aircraft.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: avionicsModel
Context triple: [Learjet 70, avionicsModel, Garmin G5000]
  • A. avionics chosen
    Indicates that an entity is related to the electronic systems used to control, monitor, or assist the operation of aircraft or spacecraft.
  • B. avionicsSupplier
    Indicates that one entity supplies avionics systems, components, or related services to another entity.
  • C. avionicsOrigin
    Indicates the source or originating location from which the avionics system or components are derived, produced, or supplied.
  • D. isPartOfAviationSystem
    Indicates that something functions as a component or subsystem within a broader aviation system or infrastructure.
  • E. aircraftConfiguration
    Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
  • F. None of above.

Provenance (6 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_69f34951348c8190b56746b0a7018182 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6a6b04c8190bee4cf9c00665ef7 completed May 3, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e511fa448190875627d9cc37c6c9 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e654e7288190ae18f37300d8bfb6 completed June 19, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34e70605548190895680498d4f6066 completed June 19, 2026, 6:51 a.m.
PD Predicate disambiguation batch_69f6d27120988190aacec621cf2bf0e8 completed May 3, 2026, 4:43 a.m.
Created at: May 1, 2026, 1:24 a.m.