Triple

T14796896
Position Surface form Disambiguated ID Type / Status
Subject Asona E347804 entity
Predicate languageContext P36 FINISHED
Object Akan language E151062 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: Akan language | Statement: [Asona, languageContext, Akan language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akan language
Context triple: [Asona, languageContext, Akan language]
  • A. Akan language chosen
    Akan is a Central Tano language of the Niger-Congo family spoken primarily in Ghana, where it serves as a major lingua franca and vehicle of Akan culture.
  • B. Akebu language
    The Akebu language is a Niger-Congo language spoken primarily by the Akebu people in parts of Togo and Ghana.
  • C. Akoko languages
    The Akoko languages are a small group of closely related Niger-Congo languages spoken primarily in the Akoko region of southwestern Nigeria.
  • D. Makhuwa-Enahara language
    The Makhuwa-Enahara language is a Bantu language spoken primarily in northern Mozambique as one of the varieties of the broader Makhuwa language cluster.
  • E. Akweya language
    Akweya language is a Niger-Congo language spoken by the Akweya people of central Nigeria and classified within the Idomoid branch.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5fdd548190a2ee5e668c2b20b4 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24c0beb0819081a124479a849bb6 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.