Triple
T21953137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | carronade |
E542116
|
entity |
| Predicate | powerComparedToLongGun |
P146674
|
FINISHED |
| Object | greater destructive effect at short range |
—
|
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: greater destructive effect at short range | Statement: [carronade, powerComparedToLongGun, greater destructive effect at short range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: powerComparedToLongGun Context triple: [carronade, powerComparedToLongGun, greater destructive effect at short range]
-
A.
weaponLength
Indicates the length or size of a weapon associated with an entity.
-
B.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
C.
hasBarrelLongerThan
Indicates that one entity’s barrel length is greater than that of another entity.
-
D.
hasSmallCalibreGuns
Indicates that the subject is equipped with or possesses guns of relatively small calibre compared to standard or typical armaments.
-
E.
gunType
Indicates the specific category or kind of gun associated with an entity.
- 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.