Triple
T12453040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabletop Mountain |
E297578
|
entity |
| Predicate | isForestType |
P57219
|
FINISHED |
| Object | northern hardwood–conifer forest zone |
—
|
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: northern hardwood–conifer forest zone | Statement: [Tabletop Mountain, isForestType, northern hardwood–conifer forest zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isForestType Context triple: [Tabletop Mountain, isForestType, northern hardwood–conifer forest zone]
-
A.
hasForestType
chosen
Indicates that an area or location is characterized by a specific type or classification of forest.
-
B.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
C.
isConifer
Indicates that the subject is a coniferous plant, typically bearing cones and having needle-like or scale-like evergreen leaves.
-
D.
isUrbanForest
Indicates that an area of trees and vegetation is located within or closely integrated with an urban or suburban environment.
-
E.
isWoodyPlant
Indicates that the subject is a plant characterized by persistent, woody stems or trunks that remain above ground year-round.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.