Triple
T28389088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Natural Bridges |
E719100
|
entity |
| Predicate | approximateSpanRange |
P172894
|
FINISHED |
| Object | 100–200 metres |
—
|
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: 100–200 metres | Statement: [Three Natural Bridges, approximateSpanRange, 100–200 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateSpanRange Context triple: [Three Natural Bridges, approximateSpanRange, 100–200 metres]
-
A.
rangeLengthApprox
chosen
Indicates that the length or extent of a range is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
B.
approximateYearRange
Indicates that the associated time span is not exact but falls within an estimated or approximate range of years.
-
C.
timePeriodApproximation
Indicates that the associated time period is an estimate or approximation rather than an exact, precise value.
-
D.
largestSpan
Indicates that the referenced entity has the greatest extent or coverage (in distance, time, or range) among a set of comparable spans.
-
E.
approximateWavelengthRange
Indicates the range of wavelengths that approximately characterizes or bounds the phenomenon, object, or interaction in question.
- 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_69eff6ef211081909d31d9be5f5567e6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 28, 2026, 1:12 a.m.