Triple
T35422637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanctuary Point |
E1023834
|
entity |
| Predicate | distanceToSydneyByRoad_km |
P15398
|
FINISHED |
| Object | approximately 200 |
—
|
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 200 | Statement: [Sanctuary Point, distanceToSydneyByRoad_km, approximately 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSydneyByRoad_km Context triple: [Sanctuary Point, distanceToSydneyByRoad_km, approximately 200]
-
A.
distanceFromSydney
chosen
Indicates the spatial distance between a given location and the city of Sydney.
-
B.
distanceToVictoriaByRoad_km
Indicates the distance in kilometers between two places when traveling by road to Victoria.
-
C.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and Brisbane.
-
D.
distanceToAdelaide_km
Indicates the physical distance, measured in kilometers, between a given location and Adelaide.
-
E.
distanceFromUluruByRoad_km
Indicates the distance in kilometers between an entity and Uluru when traveling by road rather than in a straight line.
- 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.