Triple

T14050433
Position Surface form Disambiguated ID Type / Status
Subject Rumueme E338073 entity
Predicate hasLanguage P15 FINISHED
Object Ikwerre language E414167 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: Ikwerre language | Statement: [Rumueme, hasLanguage, Ikwerre language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikwerre language
Context triple: [Rumueme, hasLanguage, Ikwerre language]
  • A. Ikwerre language chosen
    Ikwerre language is an Igboid language spoken primarily by the Ikwerre people in Rivers State, Nigeria.
  • B. Akweya language
    Akweya language is a Niger-Congo language spoken by the Akweya people of central Nigeria and classified within the Idomoid branch.
  • C. Gbagyi language
    Gbagyi language is a Central Nigerian language spoken predominantly by the Gbagyi (Gwari) people across parts of Nigeria’s Middle Belt region.
  • D. Okpamheri language
    The Okpamheri language is a lesser-known Edoid language spoken by a small ethnic community in southern Nigeria.
  • E. 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.
  • 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_69d81c664e48819088cbd8f433aeffe5 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8a518081908ad030ba48b7b946 completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d0008dc819088fcfbfe3640af47 completed May 8, 2026, 1:31 a.m.
Created at: April 9, 2026, 10:20 p.m.