Triple
T3663161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Junee–Narrandera railway line |
E77697
|
entity |
| Predicate | startPoint |
P389
|
FINISHED |
| Object | Junee |
E22225
|
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: Junee | Statement: [Junee–Narrandera railway line, startPoint, Junee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Junee Context triple: [Junee–Narrandera railway line, startPoint, Junee]
-
A.
Junee
chosen
Junee is a historic rural town in the Riverina region of New South Wales, Australia, known for its railway heritage and agricultural surroundings.
-
B.
Coffs Harbour
Coffs Harbour is a coastal city in northern New South Wales, Australia, known for its beaches, banana plantations, and the iconic Big Banana tourist attraction.
-
C.
Wagga Wagga
Wagga Wagga is a major regional city in New South Wales, Australia, known as an important agricultural, military, and transport hub in the Riverina region.
-
D.
Deniliquin
Deniliquin is a rural town in southern New South Wales, Australia, known for its agricultural industry and annual ute muster festival.
-
E.
Moree
Moree is a prominent agricultural and service town in northern New South Wales, Australia, known especially for its cotton industry and artesian hot springs.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fcd910819082012b10b23860aa |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48846af9881909d71d63b8bd8d141 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.