Triple
T12676783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuznetsov NK-144 |
E302833
|
entity |
| Predicate | aircraftSpeedClass |
P106236
|
FINISHED |
| Object | supersonic |
—
|
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: supersonic | Statement: [Kuznetsov NK-144, aircraftSpeedClass, supersonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftSpeedClass Context triple: [Kuznetsov NK-144, aircraftSpeedClass, supersonic]
-
A.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
B.
aircraftRangeCategory
Indicates the classification of an aircraft based on the distance it is capable of flying on a typical mission or with standard fuel capacity.
-
C.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
D.
ICAOClassificationSystem
Indicates a relationship where an entity is categorized or defined according to the standards and categories of the ICAO (International Civil Aviation Organization) classification system.
-
E.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:20 p.m.