Triple
T1581031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado-class battleship |
E33761
|
entity |
| Predicate | mainCaliber |
P6076
|
FINISHED |
| Object | 16-inch/45 caliber 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: 16-inch/45 caliber guns | Statement: [Colorado-class battleship, mainCaliber, 16-inch/45 caliber guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCaliber Context triple: [Colorado-class battleship, mainCaliber, 16-inch/45 caliber guns]
-
A.
gunCalibre
chosen
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
B.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
C.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
D.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
E.
mainBattle
Indicates that one battle is the primary or most significant engagement associated with a particular conflict, campaign, or 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abacfb1144819080c5687175aba1e1 |
completed | March 7, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69aa61b0f5bc8190b1dc272990a59c13 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:27 p.m.