Triple
T38337358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tooraweenah |
E1037994
|
entity |
| Predicate | distanceToGilgandra_km |
P204608
|
FINISHED |
| Object | approximately 45 |
—
|
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 45 | Statement: [Tooraweenah, distanceToGilgandra_km, approximately 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGilgandra_km Context triple: [Tooraweenah, distanceToGilgandra_km, approximately 45]
-
A.
distanceFromGundagai
Indicates the spatial distance separating something from the location of Gundagai.
-
B.
distanceFromWangaratta
Indicates the measured distance between a given location and the town of Wangaratta.
-
C.
directionFromGilgandra
Indicates the compass direction or relative bearing of one place or object as measured from the location of Gilgandra.
-
D.
distanceToGoulburn
Indicates the spatial distance between a given entity or location and the place named Goulburn.
-
E.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.