Triple
T31224088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavour-class aircraft carrier |
E796089
|
entity |
| Predicate | additionalEmbarkedPersonnelCapacity |
P171627
|
FINISHED |
| Object | up to 800 troops |
—
|
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: up to 800 troops | Statement: [Cavour-class aircraft carrier, additionalEmbarkedPersonnelCapacity, up to 800 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: additionalEmbarkedPersonnelCapacity Context triple: [Cavour-class aircraft carrier, additionalEmbarkedPersonnelCapacity, up to 800 troops]
-
A.
lifeboatCapacity
Indicates the maximum number of people or load that a lifeboat is designed and certified to safely carry.
-
B.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
C.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
D.
typicalPassengerCapacityPerShip
Indicates the usual number of passengers that a ship of a given type or class is designed or expected to carry.
-
E.
hasEmbarkedPersonnel
Indicates that one entity has taken personnel on board or loaded them for transport or deployment.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a1ac56b88190a820434b65c9fa23 |
completed | May 3, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 29, 2026, 9:10 p.m.