Triple
T402276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Navy |
E9310
|
entity |
| Predicate | operatesVessel |
P13018
|
FINISHED |
| Object | Charles de Gaulle-class aircraft carrier |
—
|
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: Charles de Gaulle-class aircraft carrier | Statement: [French Navy, operatesVessel, Charles de Gaulle-class aircraft carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesVessel Context triple: [French Navy, operatesVessel, Charles de Gaulle-class aircraft carrier]
-
A.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
B.
operatedDock
Indicates that an entity managed or controlled the functioning of a dock or docking facility.
-
C.
operatesOver
Indicates that one entity performs actions or exerts functional control across, upon, or throughout another entity or domain.
-
D.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
-
E.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eca0e2048190a7bf360257965e56 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96ee4ec8190a5c0e3f491d3963d |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.