Triple
T3373053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariposa Grove of Giant Sequoias |
E70998
|
entity |
| Predicate | numberOfGiantSequoias |
P25753
|
FINISHED |
| Object | hundreds |
—
|
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: hundreds | Statement: [Mariposa Grove of Giant Sequoias, numberOfGiantSequoias, hundreds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGiantSequoias Context triple: [Mariposa Grove of Giant Sequoias, numberOfGiantSequoias, hundreds]
-
A.
numberOfTrees
chosen
Indicates the count or quantity of trees associated with a given entity or context.
-
B.
nationalTree
Indicates that a particular tree species is officially designated as the national tree of a country or region.
-
C.
treeLongevity
Indicates the duration or lifespan of a tree, typically measured from planting or germination to death or removal.
-
D.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
E.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bdcf70819087fc7e00fbd61e0d |
completed | March 8, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69ada433059881908e46f38cc5f40a32 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.