Triple

T16767745
Position Surface form Disambiguated ID Type / Status
Subject Akassa language E407509 entity
Predicate closelyRelatedTo P37 FINISHED
Object Ogbia language E934619 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: Ogbia language | Statement: [Akassa language, closelyRelatedTo, Ogbia language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ogbia language
Context triple: [Akassa language, closelyRelatedTo, Ogbia language]
  • A. Ogbia language chosen
    The Ogbia language is a Niger-Congo language spoken primarily by the Ogbia people in Bayelsa State in Nigeria.
  • B. Gbagyi language
    Gbagyi language is a Central Nigerian language spoken predominantly by the Gbagyi (Gwari) people across parts of Nigeria’s Middle Belt region.
  • C. Igala language
    Igala language is a Niger-Congo language spoken primarily in central Nigeria by the Igala people, closely related to Yoruba and other Defoid languages.
  • D. Ogoni languages
    Ogoni languages are a small group of closely related Niger-Congo languages spoken by the Ogoni people in the Niger Delta region of southern Nigeria.
  • E. Urhobo language
    The Urhobo language is a Niger-Congo language spoken primarily by the Urhobo people of southern Nigeria, especially in Delta State.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b033d6b88190a1366a58d63b0546 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a531ea7c81908630f16f6c685d49 completed May 10, 2026, 3:33 p.m.
Created at: April 10, 2026, 5:21 a.m.