Triple
T840672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Fleet Auxiliary |
E18168
|
entity |
| Predicate | shipTypeOperated |
P13018
|
FINISHED |
| Object | fleet replenishment tankers |
—
|
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: fleet replenishment tankers | Statement: [Royal Fleet Auxiliary, shipTypeOperated, fleet replenishment tankers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipTypeOperated Context triple: [Royal Fleet Auxiliary, shipTypeOperated, fleet replenishment tankers]
-
A.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
B.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
C.
shipsWith
Indicates that one entity is delivered, packaged, or provided together with another entity as part of the same shipment or bundle.
-
D.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
E.
operatesVessel
chosen
Indicates that an agent is responsible for controlling, managing, or running the operation of a vessel.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe5d7848190b15e0cb343b6f4ba |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7dfc5c8190890c9df485d73a86 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.