Triple
T26040576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalmeny House |
E647678
|
entity |
| Predicate | estateSize |
P159896
|
FINISHED |
| Object | about 2,000 hectares |
—
|
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: about 2,000 hectares | Statement: [Dalmeny House, estateSize, about 2,000 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estateSize Context triple: [Dalmeny House, estateSize, about 2,000 hectares]
-
A.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
B.
housingArea
Indicates the geographic or spatial area associated with a housing unit or residential property.
-
C.
originalEstateSize
Indicates the total size or extent of an estate in its initial or historically original state.
-
D.
squareProperty
Indicates that one entity is the square (second power) of a numerical property or value associated with another entity.
-
E.
roofArea
Indicates the total surface area covered by the roof of a structure.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60621f3a88190abbe89d50e06422c |
completed | May 2, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 22, 2026, 9:08 a.m.