Triple

T14644145
Position Surface form Disambiguated ID Type / Status
Subject Blowering Power Station E343800 entity
Predicate locatedNear P294 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: [Blowering Power Station, locatedNear, Tumut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tumut
Context triple: [Blowering Power Station, locatedNear, 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5d5d05481908dbb23392c05d23b completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:26 a.m.