Triple
T26090800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bethanga |
E658113
|
entity |
| Predicate | distanceToWodonga |
P194233
|
FINISHED |
| Object | approximately 30 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: approximately 30 kilometres | Statement: [Bethanga, distanceToWodonga, approximately 30 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWodonga Context triple: [Bethanga, distanceToWodonga, approximately 30 kilometres]
-
A.
distanceFromWangaratta
Indicates the measured distance between a given location and the town of Wangaratta.
-
B.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
C.
distanceToWantage
Indicates the spatial distance between a given entity and the location of Wantage.
-
D.
directionToWodonga
Indicates the directional relationship pointing from a given location or entity toward Wodonga.
-
E.
distanceFromGundagai
Indicates the spatial distance separating something from the location of Gundagai.
- 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_69ee5bbfc4d08190a1b206d0ac3a1e8d |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
| PDg | Predicate description generation | batch_69fd68ab21a0819096bfc4a8c14851ad |
completed | May 8, 2026, 4:38 a.m. |
Created at: April 26, 2026, 7:47 p.m.