Triple
T33677891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barracuda-class submarine |
E862809
|
entity |
| Predicate | numberOfUnitsInClass |
P19248
|
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: [Barracuda-class submarine, numberOfUnitsInClass, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUnitsInClass Context triple: [Barracuda-class submarine, numberOfUnitsInClass, 6]
-
A.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
-
B.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
C.
hasNumberOfClassrooms
Indicates the relationship that specifies how many classrooms are associated with a given entity.
-
D.
classNumber
Indicates the numerical identifier assigned to a particular class within an educational or organizational system.
-
E.
typicalClassSize
Indicates the usual or average number of students (or participants) that are present in a single class or course section.
- 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_69f34985885c8190914322f492e04703 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a03446ec72881909c5ff25a48baadb3 |
completed | May 12, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_6a03439b393c819084aa9b7ed0d5b6b0 |
completed | May 12, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:43 a.m.