Triple
T14644862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deepak-class fleet tanker |
E343818
|
entity |
| Predicate | hasAviationFacilityFor |
P13763
|
FINISHED |
| Object | medium helicopters |
—
|
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: medium helicopters | Statement: [Deepak-class fleet tanker, hasAviationFacilityFor, medium helicopters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAviationFacilityFor Context triple: [Deepak-class fleet tanker, hasAviationFacilityFor, medium helicopters]
-
A.
aircraftFacility
chosen
Indicates that a facility is designed, equipped, or used to support the operation, maintenance, or accommodation of aircraft.
-
B.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
C.
hasGeneralAviationFacilities
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
D.
hasEmergencyAirstrip
Indicates that an entity possesses or includes an airstrip specifically designated and equipped for emergency use.
-
E.
isAviationElementOf
Indicates that something functions as a component or constituent part within a broader aviation-related system, structure, or context.
- F. None of above.
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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ea6d8481908e6331ca173c646b |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.