Triple
T15508081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulgong |
E379133
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Mudgee |
E81296
|
NE 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: Mudgee | Statement: [Gulgong, nearbyCity, Mudgee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mudgee Context triple: [Gulgong, nearbyCity, Mudgee]
-
A.
Mudgee
chosen
Mudgee is a historic town in New South Wales, Australia, renowned for its cool-climate wineries, heritage architecture, and vibrant food and wine tourism.
-
B.
Inverell
Inverell is a rural town in northern New South Wales, Australia, known for its sapphire mining and agricultural production.
-
C.
Boorowa
Boorowa is a rural town in New South Wales, Australia, known for its rich agricultural surroundings and heritage streetscapes.
-
D.
Crookwell
Crookwell is a rural town in New South Wales, Australia, known for its grazing agriculture, cool climate, and wind farms.
-
E.
Dungog
Dungog is a small rural town in New South Wales, Australia, known for its historic architecture, dairy farming, and proximity to the Barrington Tops National Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcea8888190a7b69aca360183c3 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff28d38a4819085bf051b566c17e7 |
completed | May 10, 2026, 2:50 a.m. |
Created at: April 10, 2026, 3:55 a.m.