Triple
T591105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biltmore Estate |
E17271
|
entity |
| Predicate | originalEstateArea |
P175
|
FINISHED |
| Object | approximately 125,000 acres |
—
|
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 125,000 acres | Statement: [Biltmore Estate, originalEstateArea, approximately 125,000 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalEstateArea Context triple: [Biltmore Estate, originalEstateArea, approximately 125,000 acres]
-
A.
representedArea
Indicates that one entity serves as a representation or depiction of a particular area or region.
-
B.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
C.
occupiesFormerEstateOf
Indicates that one entity currently resides in, uses, or controls a property that was previously the estate of another entity.
-
D.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
E.
areaApprox
Indicates that one entity’s area is approximately equal to the area of another entity.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bb8ff0081909cd53d88930e2693 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.