Triple
T29862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | giant sequoia |
E596
|
entity |
| Predicate | maximumTrunkDiameter |
P1978
|
FINISHED |
| Object | about 8 meters at breast height |
—
|
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 8 meters at breast height | Statement: [giant sequoia, maximumTrunkDiameter, about 8 meters at breast height]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumTrunkDiameter Context triple: [giant sequoia, maximumTrunkDiameter, about 8 meters at breast height]
-
A.
plantHeight
Indicates the measured vertical size or growth extent of a plant from its base to its top.
-
B.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
C.
maximumDepth
Indicates the greatest extent or deepest level reached by something within a given context or structure.
-
D.
heightWithPedestal
Indicates the total vertical measurement of an object including the height of its supporting pedestal.
-
E.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486d40348190b2d21fc444f499a6 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a248fef2b881908180bd4e32e58cb5 |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.