Triple
T16444517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montana-class battleship |
E399389
|
entity |
| Predicate | plannedNumberOfShips |
P21287
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Montana-class battleship, plannedNumberOfShips, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedNumberOfShips Context triple: [Montana-class battleship, plannedNumberOfShips, 5]
-
A.
numberOfPlannedShips
chosen
Indicates the total count of ships that are intended or scheduled to be built, deployed, or used according to a plan.
-
B.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
C.
classShipCount
Indicates the number of ships associated with a particular class or category.
-
D.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
-
E.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cd9d474819091b4a80de1019c54 |
completed | April 18, 2026, 7:03 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:10 a.m.