Triple
T15005107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byfield |
E377687
|
entity |
| Predicate | distanceToYeppoon_km |
P116327
|
FINISHED |
| Object | approximately 30 |
—
|
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 | Statement: [Byfield, distanceToYeppoon_km, approximately 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToYeppoon_km Context triple: [Byfield, distanceToYeppoon_km, approximately 30]
-
A.
distanceToGympie
Indicates the spatial distance between a given location and the town or area of Gympie.
-
B.
distanceToBrisbane_km
Indicates the physical distance, measured in kilometers, between a given location and Brisbane.
-
C.
distanceToForster_km
Indicates the physical distance, measured in kilometers, between an entity and a reference location named Forster.
-
D.
distanceFromWaggaWagga_km
Indicates the numerical distance, measured in kilometers, between an entity’s location and Wagga Wagga.
-
E.
distanceToKempsey
Indicates the spatial distance between a given entity or location and the town of Kempsey.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7322b5c81909089cbbf816e1436 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:54 a.m.