Triple
T1053352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 747 |
E22746
|
entity |
| Predicate | totalProducedApprox |
P2091
|
FINISHED |
| Object | over 1500 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: over 1500 units | Statement: [Boeing 747, totalProducedApprox, over 1500 units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalProducedApprox Context triple: [Boeing 747, totalProducedApprox, over 1500 units]
-
A.
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.
-
B.
massProduced
Indicates that an item is manufactured in large quantities, typically using standardized, industrial production processes.
-
C.
numberOfIsotopesProduced
Indicates the quantity of distinct isotopes that are generated or obtained from a specified process, reaction, or source.
-
D.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
E.
numberBuilt
chosen
Indicates the total count of items or structures that have been constructed or produced.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b644088190a1f0f00f97941298 |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.