Triple
T1530838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMX-1 |
E32437
|
entity |
| Predicate | aircraftMarking |
P29893
|
FINISHED |
| Object | green and white presidential helicopter livery |
—
|
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: green and white presidential helicopter livery | Statement: [HMX-1, aircraftMarking, green and white presidential helicopter livery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftMarking Context triple: [HMX-1, aircraftMarking, green and white presidential helicopter livery]
-
A.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
B.
aircraftRegistration
Indicates that an aircraft is assigned a specific official registration identifier or code.
-
C.
notableAircraftCallsign
Indicates that a particular aircraft is notably associated with, or commonly identified by, a specific callsign.
-
D.
aircraftDesignationPrefix
Indicates the standardized prefix used in an aircraft’s designation that conveys its type, role, or function.
-
E.
ICAOTypeDesignator
Indicates the standardized aircraft type code assigned by ICAO that specifies the model or family of an aircraft used in aviation operations and documentation.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a933ddc5a881909cdf503f2bc29bd4 |
completed | March 5, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69a907ae8f688190ad9000ea1e018585 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a933dce3488190b20f0e3d37d16371 |
completed | March 5, 2026, 7:42 a.m. |
Created at: March 4, 2026, 7:26 p.m.