Triple
T764385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Isa |
E16141
|
entity |
| Predicate | distanceToTown |
P7750
|
FINISHED |
| Object | about 900 km west of Townsville |
—
|
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 900 km west of Townsville | Statement: [Mount Isa, distanceToTown, about 900 km west of Townsville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTown Context triple: [Mount Isa, distanceToTown, about 900 km west of Townsville]
-
A.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
B.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
-
C.
distance
chosen
Indicates the spatial separation or length between two points, objects, or locations.
-
D.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
E.
distanceFromTerminus
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a69dfeb08190b54a476cfa66e6d6 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a506106081909ef97a679ff00a5a |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.