Triple
T38066807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Rim Road |
E950490
|
entity |
| Predicate | approximatelyLength |
P189304
|
FINISHED |
| Object | 100 miles |
—
|
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: 100 miles | Statement: [White Rim Road, approximatelyLength, 100 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximatelyLength Context triple: [White Rim Road, approximatelyLength, 100 miles]
-
A.
longitudAproximada
chosen
Indicates an approximate measurement of the length of something, rather than its exact value.
-
B.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
C.
rangeLengthApprox
Indicates that the length or extent of a range is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
D.
alignedApproximately
Indicates that two or more entities are positioned or oriented in roughly the same direction or arrangement, allowing for minor deviations or imprecision.
-
E.
approximateWidthMeters
Indicates an estimated measurement of an entity’s width expressed in meters.
- 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_69f76f01e63c819093b6012fc974f35a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffed8912488190baa05f572e5b1b89 |
completed | May 10, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69ffed12a76c8190ad85c6ac869c72e9 |
completed | May 10, 2026, 2:27 a.m. |
Created at: May 3, 2026, 4:21 p.m.