Triple

T6749005
Position Surface form Disambiguated ID Type / Status
Subject Mauritian rupee E154293 entity
Predicate languageOfName P15 FINISHED
Object Mauritian Creole E86042 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: Mauritian Creole | Statement: [Mauritian rupee, languageOfName, Mauritian Creole]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mauritian Creole
Context triple: [Mauritian rupee, languageOfName, Mauritian Creole]
  • A. Mauritian Creole chosen
    Mauritian Creole is a French-based creole language spoken primarily in Mauritius, serving as the country’s most widely used lingua franca and a key marker of its cultural identity.
  • B. Seychellois Creole
    Seychellois Creole is a French-based creole language spoken primarily in Seychelles, where it serves as a national and widely used lingua franca.
  • C. Réunion Creole
    Réunion Creole is a French-based creole language spoken by the majority of the population on the island of Réunion in the Indian Ocean.
  • D. Guianan Creole
    Guianan Creole is a French-based creole language spoken primarily in French Guiana, shaped by African, Amerindian, and European influences.
  • E. Kreol Morisien
    Kreol Morisien is a French-based Creole language spoken primarily in Mauritius and serves as the country’s most widely used lingua franca.
  • 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_69c6880ef37881909268a5a7299b9293 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1d8bfa48190a7fc48102258ae17 completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b180f188190b380909c46fbce40 completed March 27, 2026, 10:56 p.m.
Created at: March 27, 2026, 2:11 p.m.