Triple
T12043660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Grant Tree |
E286728
|
entity |
| Predicate | volumeOfTrunk |
P5642
|
FINISHED |
| Object | over 46,000 cubic feet |
—
|
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 46,000 cubic feet | Statement: [General Grant Tree, volumeOfTrunk, over 46,000 cubic feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volumeOfTrunk Context triple: [General Grant Tree, volumeOfTrunk, over 46,000 cubic feet]
-
A.
trunkVolume
chosen
Indicates the volume or capacity of an entity’s trunk or main storage compartment.
-
B.
hasTrunk
Indicates that one entity possesses or is equipped with a trunk as a physical feature or component.
-
C.
trunkCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a trunk (such as that of a tree or similar object).
-
D.
trunkDiameter
Indicates the measured thickness of a trunk, typically expressed as the diameter across its cross-section.
-
E.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.