Triple
T21953140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | carronade |
E542116
|
entity |
| Predicate | crewSizeComparedToLongGun |
P146677
|
FINISHED |
| Object | smaller crew required |
—
|
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: smaller crew required | Statement: [carronade, crewSizeComparedToLongGun, smaller crew required]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewSizeComparedToLongGun Context triple: [carronade, crewSizeComparedToLongGun, smaller crew required]
-
A.
hasSmallCalibreGuns
Indicates that the subject is equipped with or possesses guns of relatively small calibre compared to standard or typical armaments.
-
B.
numberOfGuns
Indicates the quantity of guns associated with a given entity or situation.
-
C.
typicalRifleWeightLimit
Indicates the maximum weight that is generally considered standard or acceptable for a typical rifle.
-
D.
weaponLength
Indicates the length or size of a weapon associated with an entity.
-
E.
barrelCountComparedToGAU-12/U
Indicates how the number of barrels of an entity compares to that of the GAU-12/U weapon system.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243d43d8819084e280b129631288 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb9b75308190addc3dba7b5d5ddd |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:59 p.m.