Triple
T18090554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crowley’s Ridge |
E432952
|
entity |
| Predicate | notableVegetation |
P953
|
FINISHED |
| Object | oak-hickory forest |
—
|
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: oak-hickory forest | Statement: [Crowley’s Ridge, notableVegetation, oak-hickory forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVegetation Context triple: [Crowley’s Ridge, notableVegetation, oak-hickory forest]
-
A.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
B.
famousPlants
Indicates that the plants in question are widely known or celebrated, typically for their distinctive characteristics, history, or cultural significance.
-
C.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
D.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd17ba98819085a15e8593d98259 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.