Triple
T32170756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirror Lakes |
E821702
|
entity |
| Predicate | approximateDistanceFromTeAnau |
P197330
|
FINISHED |
| Object | about 56 kilometres |
—
|
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 56 kilometres | Statement: [Mirror Lakes, approximateDistanceFromTeAnau, about 56 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceFromTeAnau Context triple: [Mirror Lakes, approximateDistanceFromTeAnau, about 56 kilometres]
-
A.
distanceToTekapo_km
Indicates the physical distance, measured in kilometers, between a given entity and Tekapo.
-
B.
distanceToGreymouth
Indicates the spatial distance between a given entity or location and the town of Greymouth.
-
C.
distanceToTimaru_km
Indicates the physical distance, measured in kilometers, between a given location and Timaru.
-
D.
distanceFromKaitaia
Indicates the measured distance between a given location or entity and Kaitaia.
-
E.
distanceToWaipukurau
Indicates the spatial distance between a given location or entity and Waipukurau.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe87b609888190913b0c3f787ecdba |
completed | May 9, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69fe8731af48819092084f6f74bf052d |
completed | May 9, 2026, 1 a.m. |
| PDg | Predicate description generation | batch_69fe87b52bd4819087d6d338fe47c97c |
completed | May 9, 2026, 1:02 a.m. |
Created at: May 1, 2026, 12:33 a.m.