Triple

T9269054
Position Surface form Disambiguated ID Type / Status
Subject Bade E222774 entity
Predicate hasNeighboringLanguage P16383 FINISHED
Object Ngizim E222773 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: Ngizim | Statement: [Bade, hasNeighboringLanguage, Ngizim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngizim
Context triple: [Bade, hasNeighboringLanguage, Ngizim]
  • A. Ngizim chosen
    Ngizim is a West Chadic language spoken primarily by the Ngizim people in northeastern Nigeria.
  • B. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • C. Zvongombe
    Zvongombe was the principal urban and political center of the Mutapa Kingdom in what is now northern Zimbabwe.
  • D. Mvila
    Mvila is an administrative department in Cameroon's South Region, known for its local governance role and regional cultural diversity.
  • E. Bulange
    Bulange is the historic administrative building of the Buganda Kingdom in Kampala, Uganda, serving as the seat of the Lukiiko (parliament) and the Kabaka’s offices.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd074ef7408190b213c09491918132 completed April 1, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0c743c76c8190b39cfe25c6ab1db2 completed April 4, 2026, 8:09 a.m.
Created at: March 30, 2026, 7:33 p.m.