Triple
T2872599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sachertorte |
E56797
|
entity |
| Predicate | hasTypicalDiameter |
P7302
|
FINISHED |
| Object | about 22 to 24 centimeters |
—
|
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: about 22 to 24 centimeters | Statement: [Sachertorte, hasTypicalDiameter, about 22 to 24 centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalDiameter Context triple: [Sachertorte, hasTypicalDiameter, about 22 to 24 centimeters]
-
A.
approximateDiameter
chosen
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
B.
hasTypicalColumnHeightToDiameterRatio
Indicates that there is a characteristic or commonly observed proportional relationship between a column’s height and its diameter.
-
C.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
D.
meanDiameter_km
Indicates the average diameter of an object or region measured in kilometers.
-
E.
sphereDiameter
Indicates the measurement of the distance across a sphere passing through its center, relating the sphere to its diameter.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abdfe59ef88190b8bdfdd03e8965f3 |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:03 p.m.