Triple

T11302745
Position Surface form Disambiguated ID Type / Status
Subject Southern Gur languages E267635 entity
Predicate hasLanguage P15 FINISHED
Object Kassena language E267646 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: Kassena language | Statement: [Southern Gur languages, hasLanguage, Kassena language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kassena language
Context triple: [Southern Gur languages, hasLanguage, Kassena language]
  • A. Kasem language chosen
    Kasem is a Gur language of the Niger-Congo family spoken primarily in parts of Burkina Faso and Ghana.
  • B. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • C. Katcha language
    The Katcha language is a Kadu (Kadugli) language spoken by the Katcha people of the Nuba Mountains region in Sudan.
  • D. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • E. Kaxabu language
    The Kaxabu language is an indigenous Formosan language of Taiwan spoken by the Kaxabu people and considered highly endangered.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9a5c3788190ba54eda514b97903 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525a842dc81909c84d8bd1a6414fa completed April 19, 2026, 6:57 p.m.
Created at: April 8, 2026, 9:32 p.m.