Triple

T11302734
Position Surface form Disambiguated ID Type / Status
Subject Southern Gur languages E267635 entity
Predicate hasLanguage P15 FINISHED
Object Kabre language E267643 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: Kabre language | Statement: [Southern Gur languages, hasLanguage, Kabre language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabre language
Context triple: [Southern Gur languages, hasLanguage, Kabre language]
  • A. Kaba language
    The Kaba language is a Central Sudanic language spoken primarily in parts of Chad and the Central African Republic by Kaba ethnic groups.
  • B. Kabye language chosen
    Kabye language is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
  • C. Kabba language
    Kabba is a Niger-Congo language of the Adamawa–Ubangi branch spoken primarily in the Central African Republic.
  • D. Ikwerre language
    Ikwerre language is an Igboid language spoken primarily by the Ikwerre people in Rivers State, Nigeria.
  • 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_69e50a57366081908a05fc52c5d4074c completed April 19, 2026, 5:01 p.m.
Created at: April 8, 2026, 9:32 p.m.