Triple
T556964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Riverina |
E11962
|
entity |
| Predicate | includesTown |
P847
|
FINISHED |
| Object | Leeton |
E21140
|
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: Leeton | Statement: [Division of Riverina, includesTown, Leeton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leeton Context triple: [Division of Riverina, includesTown, Leeton]
-
A.
Leeton
chosen
Leeton is a regional agricultural town in the Riverina area of New South Wales, Australia, known for its irrigated farming and food production.
-
B.
Helensvale
Helensvale is a residential suburb and transport hub in the northern part of the Gold Coast in Queensland, Australia.
-
C.
Yass
Yass is a historic town in New South Wales, Australia, known as a regional service centre in the Southern Tablelands.
-
D.
Tenterfield
Tenterfield is a historic rural town in New South Wales, Australia, known for its heritage architecture and role in Australian federation history.
-
E.
Deniliquin
Deniliquin is a rural town in southern New South Wales, Australia, known for its agricultural industry and annual ute muster festival.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d28af148190acad3cfb809ff2f2 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a734f6c8190a141dafc03dd2e77 |
completed | March 2, 2026, 9:37 a.m. |
Created at: March 1, 2026, 7:32 p.m.