Triple
T1272403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Pampanito |
E15737
|
entity |
| Predicate | numberOfWarPatrols |
P28076
|
FINISHED |
| Object | 6 |
—
|
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 | Statement: [USS Pampanito, numberOfWarPatrols, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWarPatrols Context triple: [USS Pampanito, numberOfWarPatrols, 6]
-
A.
navalVesselsAlliedApprox
Indicates that two or more naval vessels are approximately allied, suggesting a cooperative or friendly relationship without specifying a precise or formal alliance.
-
B.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
C.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
-
D.
antiSubmarineArmament
Indicates the type or presence of weapons or equipment specifically designed for anti-submarine warfare associated with an entity.
-
E.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06c033081909bc594157abaf5bb |
completed | March 1, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:50 p.m.