Triple

T16767600
Position Surface form Disambiguated ID Type / Status
Subject Nembe language E407505 entity
Predicate closelyRelatedTo P37 FINISHED
Object Izon language E407507 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: Izon language | Statement: [Nembe language, closelyRelatedTo, Izon language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Izon language
Context triple: [Nembe language, closelyRelatedTo, Izon language]
  • A. Izon language chosen
    The Izon language is a major Niger-Congo language spoken primarily by the Ijaw people of the Niger Delta region in southern Nigeria.
  • B. Isoko language
    The Isoko language is a Niger-Congo language spoken primarily by the Isoko people of southern Nigeria, particularly in Delta State.
  • C. Zaiwa language
    The Zaiwa language is a Tibeto-Burman language spoken primarily by the Zaiwa people in parts of Yunnan, China and northern Myanmar.
  • D. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • E. Siona language
    The Siona language is a Western Tucanoan indigenous language spoken by the Siona people of the Amazonian region of Ecuador and Colombia.
  • 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.