Triple
T830708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B-29 Superfortress |
E17956
|
entity |
| Predicate | productionNumber |
P2091
|
FINISHED |
| Object | approximately 3970 units |
—
|
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: approximately 3970 units | Statement: [B-29 Superfortress, productionNumber, approximately 3970 units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionNumber Context triple: [B-29 Superfortress, productionNumber, approximately 3970 units]
-
A.
serialNumber
Indicates a unique identifying code assigned to an individual item or instance within a series or batch.
-
B.
modelNumber
Indicates that one entity is the specific model identifier or code assigned to another entity (such as a product or device).
-
C.
massProduced
Indicates that an item is manufactured in large quantities, typically using standardized, industrial production processes.
-
D.
numberBuilt
chosen
Indicates the total count of items or structures that have been constructed or produced.
-
E.
totalProduction
Indicates the overall quantity of goods, services, or output produced by an entity or system over a specified period or within a defined scope.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb384988190949d2df65662f76d |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.