Triple

T14664037
Position Surface form Disambiguated ID Type / Status
Subject Atyap proper E344317 entity
Predicate language P15 FINISHED
Object Atyap language E344315 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: Atyap language | Statement: [Atyap proper, language, Atyap language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atyap language
Context triple: [Atyap proper, language, Atyap language]
  • A. Attié language
    The Attié language is a Niger-Congo language spoken primarily by the Attié people of southern Côte d'Ivoire.
  • B. Atorada language
    The Atorada language is an indigenous Arawakan language of South America, closely associated with the Wapishana people and now highly endangered or possibly extinct.
  • C. Agatu language
    The Agatu language is a Niger-Congo language spoken by the Agatu people of central Nigeria, belonging to the Idomoid branch.
  • D. Tyap language chosen
    Tyap language is a Plateau language of the Niger-Congo family spoken predominantly by the Atyap people in southern Kaduna State, Nigeria.
  • E. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54ae5ac81908cc69891f280e5f7 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5e4789481909a64622a1d284373 completed May 8, 2026, 12:24 p.m.
Created at: April 10, 2026, 1:27 a.m.