Triple
T8768712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Reef |
E208401
|
entity |
| Predicate | distanceFromAustralianMainland_km |
P56865
|
FINISHED |
| Object | approximately 270 |
—
|
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 270 | Statement: [Scott Reef, distanceFromAustralianMainland_km, approximately 270]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromAustralianMainland_km Context triple: [Scott Reef, distanceFromAustralianMainland_km, approximately 270]
-
A.
distanceFromNewZealandMainland_km
Indicates the distance, measured in kilometers, between an entity’s location and the mainland of New Zealand.
-
B.
distanceToAustralia
chosen
Indicates the measured or estimated spatial distance between a given entity and Australia.
-
C.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
D.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
E.
distanceToForster_km
Indicates the physical distance, measured in kilometers, between an entity and a reference location named Forster.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5eec49708190ba760d81a7974c50 |
completed | March 31, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:41 p.m.