Triple

T21053695
Position Surface form Disambiguated ID Type / Status
Subject Ngulu language E518652 entity
Predicate hasAlternateName P39 FINISHED
Object Nguru NE NERFINISHED

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: Nguru | Statement: [Ngulu language, hasAlternateName, Nguru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nguru
Context triple: [Ngulu language, hasAlternateName, Nguru]
  • A. Nguru chosen
    Nguru is a town and local government area in northeastern Nigeria known as a commercial hub and railway terminus in Yobe State.
  • B. Wawona
    Wawona is a historic community and visitor area within Yosemite National Park in California, known for its scenic meadows, giant sequoias, and proximity to natural and cultural landmarks.
  • C. Nakasero
    Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
  • D. Mataranka
    Mataranka is a small town in Australia's Northern Territory, known for its thermal springs and location near Elsey National Park.
  • E. Takura
    Takura is a rural locality in Queensland, Australia, situated near the community associated with Howard.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5053ac48190921529544959e906 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fd7e087c81908712ddc63e8b1e6c completed April 21, 2026, 4:30 a.m.
Created at: April 16, 2026, 2:36 p.m.