Triple
T13602729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Navy Carrier Strike Group |
E324983
|
entity |
| Predicate | typicalEscortRole |
P18942
|
FINISHED |
| Object | air defence |
—
|
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: air defence | Statement: [Royal Navy Carrier Strike Group, typicalEscortRole, air defence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEscortRole Context triple: [Royal Navy Carrier Strike Group, typicalEscortRole, air defence]
-
A.
typicalRole
chosen
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
B.
typicalPerformerRoleType
Indicates the usual or characteristic role type that a performer commonly plays or is associated with in their performances.
-
C.
typicalAnnouncerRole
Indicates that an entity commonly or characteristically serves in a particular announcer role in relevant contexts.
-
D.
roleInAtomicBlonde
Indicates that an entity has a specific role or participation in the film "Atomic Blonde."
-
E.
roleInLasVegas
Indicates that an entity holds or held a specific role, position, or function within the context of Las Vegas (such as in its government, organizations, events, or productions).
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.