Triple
T33070035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cessna Citation business jets |
E846209
|
entity |
| Predicate | typicalSizeClass |
P206340
|
FINISHED |
| Object | light jet |
—
|
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: light jet | Statement: [Cessna Citation business jets, typicalSizeClass, light jet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSizeClass Context triple: [Cessna Citation business jets, typicalSizeClass, light jet]
-
A.
figureSizeClass
Indicates the classification of a figure based on its relative or absolute size within a given context.
-
B.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
C.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
D.
typicalCellSize
Indicates the usual or characteristic physical size associated with a given cell.
-
E.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:25 a.m.