Triple
T1419128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adirondack Park |
E31983
|
entity |
| Predicate | percentagePrivateLand |
P27563
|
FINISHED |
| Object | approximately 55 percent |
—
|
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: approximately 55 percent | Statement: [Adirondack Park, percentagePrivateLand, approximately 55 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentagePrivateLand Context triple: [Adirondack Park, percentagePrivateLand, approximately 55 percent]
-
A.
percentageOfLandInNationalPark
Indicates the proportion of a given area’s total land that lies within designated national park boundaries.
-
B.
requiredShareOfLand
Indicates the proportion or amount of land that must be allocated or possessed to satisfy a specified requirement or rule.
-
C.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
-
D.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
E.
primaryLandUse
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c40631e881909ddf81a2eb84af1c |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:59 p.m.