Triple
T14615769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tumut 3 Power Station |
E343080
|
entity |
| Predicate | nearTown |
P2064
|
FINISHED |
| Object | Tumut |
E71309
|
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: Tumut | Statement: [Tumut 3 Power Station, nearTown, Tumut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tumut Context triple: [Tumut 3 Power Station, nearTown, Tumut]
-
A.
Tumut
chosen
Tumut is a historic town in the Snowy Mountains region of New South Wales, Australia, known for its timber industry, scenic river landscapes, and role as a gateway to the Snowy Mountains Scheme.
-
B.
Githunguri
Githunguri is a town in Kenya known for its agricultural activities, particularly dairy and coffee farming, within Kiambu County.
-
C.
Totila
Totila was a 6th-century king of the Ostrogoths best known for his dynamic military leadership and central role in the later stages of the Gothic War against the Byzantine Empire.
-
D.
Turtkul
Turtkul is a city in the autonomous Republic of Karakalpakstan in northwestern Uzbekistan, known as a regional center near the Amu Darya River.
-
E.
Nakasero
Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb46439b88190a4affcc7ccedab6b |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda922f29c8190af98a8241d86f7cd |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:25 a.m.