Triple

T2819115
Position Surface form Disambiguated ID Type / Status
Subject Francophone Africa E54363 entity
Predicate hasLinguaFrancaRole P24056 FINISHED
Object interethnic communication LITERAL 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: interethnic communication | Statement: [Francophone Africa, hasLinguaFrancaRole, interethnic communication]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLinguaFrancaRole
Context triple: [Francophone Africa, hasLinguaFrancaRole, interethnic communication]
  • A. isLinguaFrancaOf chosen
    Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
  • B. hasOfficerLanguage
    Indicates that an officer is able or authorized to communicate in a specified language.
  • C. hasMemberLanguage
    Indicates that one entity is a language that is a constituent or member of a larger language group, family, or collection represented by the other entity.
  • D. hasLinguist
    Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
  • E. isLanguageOf
    Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
  • F. None of above.

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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abdf15b7288190a03d1193cc0544a6 completed March 7, 2026, 8:17 a.m.
PD Predicate disambiguation batch_69abdd08f2f481908c3da8a9c7a00552 completed March 7, 2026, 8:08 a.m.
Created at: March 6, 2026, 9:59 p.m.