Triple

T12480896
Position Surface form Disambiguated ID Type / Status
Subject Gombe Local Government Area E298300 entity
Predicate administrativeCentre P1474 FINISHED
Object Gombe E61525 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: Gombe | Statement: [Gombe Local Government Area, administrativeCentre, Gombe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gombe
Context triple: [Gombe Local Government Area, administrativeCentre, Gombe]
  • A. Gombe
    Gombe is a region in western Tanzania best known for its national park where pioneering primatologist Jane Goodall conducted her landmark chimpanzee research.
  • B. Gombe chosen
    Gombe is a major city in northeastern Nigeria that serves as the capital and economic hub of Gombe State.
  • C. Mbewuleni
    Mbewuleni is a rural village in South Africa’s Eastern Cape province, best known as the birthplace of former South African president Thabo Mbeki.
  • D. Nyala
    Nyala is a major city in western Sudan that serves as a key commercial and administrative center in the Darfur region.
  • E. Mambasa
    Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcdcd3c81908ad29145db241408 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556c8e4c8190aa7df1defb4cce78 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.