Triple

T8390526
Position Surface form Disambiguated ID Type / Status
Subject Nimba County E197930 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Yekepa E730800 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: Yekepa | Statement: [Nimba County, hasUrbanCenter, Yekepa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yekepa
Context triple: [Nimba County, hasUrbanCenter, Yekepa]
  • A. Yekepa chosen
    Yekepa is a mining town in northern Liberia known for its rich iron ore deposits and company-operated facilities.
  • B. Akpabuyo
    Akpabuyo is a coastal local government area in southeastern Nigeria known for its location near Calabar in Cross River State.
  • C. Kgalema
    Kgalema is a South African politician who served as the country's third post-apartheid president and later as deputy president.
  • D. Longuda
    Longuda are an ethnic group in northeastern Nigeria, primarily known for their distinct language and cultural presence in and around Adamawa State.
  • E. Kabnis
    Kabnis is a central character in Jean Toomer's modernist work "Cane," representing the struggles of a Northern-educated Black man confronting the racial and cultural realities of the rural American South.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb810c5c5c81908e124c64911c4e6c completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02cb3a1481908d30993d47c70039 completed April 2, 2026, 5:46 a.m.
Created at: March 30, 2026, 6:03 p.m.