Triple
T8234928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orion-class battleship |
E192380
|
entity |
| Predicate | typicalCrewComplement |
P883
|
FINISHED |
| Object | approximately 900–1,100 officers and men |
—
|
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: approximately 900–1,100 officers and men | Statement: [Orion-class battleship, typicalCrewComplement, approximately 900–1,100 officers and men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCrewComplement Context triple: [Orion-class battleship, typicalCrewComplement, approximately 900–1,100 officers and men]
-
A.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
B.
crewCountApproximate
chosen
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
totalCrewMembers
Indicates the total number of crew members associated with a given entity or context.
-
D.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
E.
carriesCrewOf
Indicates that one entity serves as the vehicle or vessel that transports the crew belonging to another entity.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb782931848190bcc54622f34e06a7 |
completed | March 31, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69cb36b1dea0819091418072501e79c1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:46 p.m.