Triple

T13024870
Position Surface form Disambiguated ID Type / Status
Subject Auchi E326275 entity
Predicate languageSpoken P151 FINISHED
Object Etsako language E975842 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: Etsako language | Statement: [Auchi, languageSpoken, Etsako language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Etsako language
Context triple: [Auchi, languageSpoken, Etsako language]
  • A. Etsako language chosen
    Etsako language is an Edoid language of southern Nigeria spoken primarily by the Etsako people in Edo State.
  • B. Igarra language
    The Igarra language is an Edoid language spoken primarily by the Igarra people in Akoko-Edo Local Government Area of Edo State, Nigeria.
  • C. Isoko language
    The Isoko language is a Niger-Congo language spoken primarily by the Isoko people of southern Nigeria, particularly in Delta State.
  • D. Lotuko language
    The Lotuko language is an Eastern Nilotic language spoken primarily by the Lotuko people of South Sudan.
  • E. Itzaʼ language
    The Itzaʼ language is a critically endangered Mayan language of the Yucatecan branch, traditionally spoken by the Itza people of Guatemala’s Petén region.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97efac71881908a21d70c3c6ce099 completed April 10, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c11c1f6c8190be1c570a7e44a313 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:53 p.m.