Triple
T994622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Forest sequoia grove |
E21467
|
entity |
| Predicate | otherTreeSpecies |
P966
|
FINISHED |
| Object | ponderosa pine |
—
|
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: ponderosa pine | Statement: [Giant Forest sequoia grove, otherTreeSpecies, ponderosa pine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherTreeSpecies Context triple: [Giant Forest sequoia grove, otherTreeSpecies, ponderosa pine]
-
A.
notableTreeSpecies
chosen
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
B.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
-
C.
isPlantOf
Indicates that one entity is a plant that belongs to, is associated with, or is characteristic of another entity (such as a region, habitat, or owner).
-
D.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
hasTrees
Indicates that something possesses or contains one or more trees.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c75de88190bf7fec7a053f7a90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.