Triple
T11353663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town-class cruiser (1930s) |
E268897
|
entity |
| Predicate | typicalMainBatteryCaliber |
P6076
|
FINISHED |
| Object | 6-inch guns |
—
|
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: 6-inch guns | Statement: [Town-class cruiser (1930s), typicalMainBatteryCaliber, 6-inch guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMainBatteryCaliber Context triple: [Town-class cruiser (1930s), typicalMainBatteryCaliber, 6-inch guns]
-
A.
gunCalibre
chosen
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
B.
numberOfMainBatteryGuns
Indicates the quantity of primary (main) battery guns that an entity, typically a warship or similar platform, is equipped with.
-
C.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
D.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
E.
mainGunModel
Indicates the specific model or type designation of the primary gun or main weapon system used by an 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.