Triple

T23348719
Position Surface form Disambiguated ID Type / Status
Subject Duala (Cameroon) E591942 entity
Predicate neighboringLanguages P16383 FINISHED
Object Basaa language NE NERFINISHED

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: Basaa language | Statement: [Duala (Cameroon), neighboringLanguages, Basaa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Basaa language
Context triple: [Duala (Cameroon), neighboringLanguages, Basaa language]
  • A. Basaa chosen
    Basaa is a Bantu language spoken primarily by the Basaa people in Cameroon.
  • B. Bassa language
    The Bassa language is a Bantu language spoken by the Bassa people of central Cameroon.
  • C. Bassa language
    Bassa language is a Kru language of the Niger-Congo family spoken primarily by the Bassa people in Liberia and neighboring regions.
  • D. Barai language
    The Barai language is an indigenous Papuan language spoken by communities in southeastern Papua New Guinea.
  • E. Sa’ban language
    The Sa’ban language is an Austronesian language spoken by the Sa’ban people of Borneo, particularly in parts of Malaysian Sarawak and Indonesian Kalimantan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e25d20e3d08190bcede87673cafb25 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f199cb2a3c8190a5c0c8d8735256c7 completed April 29, 2026, 5:40 a.m.
Created at: April 17, 2026, 5:19 p.m.