Triple
T14146170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarago |
E350554
|
entity |
| Predicate | distanceToGoulburn |
P112996
|
FINISHED |
| Object | approximately 40 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 40 kilometres | Statement: [Tarago, distanceToGoulburn, approximately 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGoulburn Context triple: [Tarago, distanceToGoulburn, approximately 40 kilometres]
-
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.
distanceFromAlbury
Indicates the spatial distance between a given entity or location and the place named Albury.
-
D.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
E.
distanceToMildura_km
Indicates the physical distance, measured in kilometers, between a given location and Mildura.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de612266248190a8591b646fe30ae6 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 12:54 a.m.