Triple
T165556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Sherman Tree |
E3006
|
entity |
| Predicate | baseCircumference |
P5643
|
FINISHED |
| Object | about 31.3 meters |
—
|
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 31.3 meters | Statement: [General Sherman Tree, baseCircumference, about 31.3 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baseCircumference Context triple: [General Sherman Tree, baseCircumference, about 31.3 meters]
-
A.
tunnelCircumference
Indicates the circular distance around the inner boundary of a tunnel’s cross-section.
-
B.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
C.
hasEquatorialCircumference
Indicates that one entity has a specified measurement for its circumference at the equator.
-
D.
wheelbase
Indicates the distance between the centers of the front and rear wheels of a vehicle.
-
E.
hasEquatorialRadius
Indicates that an entity has a specified radius measured at its equator.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a25883ac8481909616b2179561bd98 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25664ba8081908ac298511a9fc5ba |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256eb46ec81909c730000e5041d0d |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.