Triple
T27601637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Plane Tree of Telavi |
E700060
|
entity |
| Predicate | trunkCircumference |
P46315
|
FINISHED |
| Object | about 12 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 12 meters | Statement: [Giant Plane Tree of Telavi, trunkCircumference, about 12 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trunkCircumference Context triple: [Giant Plane Tree of Telavi, trunkCircumference, about 12 meters]
-
A.
trunkDiameter
Indicates the measured thickness of a trunk, typically expressed as the diameter across its cross-section.
-
B.
trunkVolume
Indicates the volume or capacity of an entity’s trunk or main storage compartment.
-
C.
hasTrunk
Indicates that one entity possesses or is equipped with a trunk as a physical feature or component.
-
D.
trunkCharacteristic
chosen
Indicates a relationship where a specific characteristic or property is attributed to a trunk (such as that of a tree or similar object).
-
E.
maximumTrunkDiameter
Indicates the largest thickness of a trunk measured across its widest point.
- 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_69ef6a4e2e208190b63b7268f405785c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63096763c8190befb3934bfdc9350 |
completed | May 2, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:08 p.m.