Triple

T21635922
Position Surface form Disambiguated ID Type / Status
Subject MGA E533957 entity
Predicate languageContext P36 FINISHED
Object Malagasy 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: Malagasy | Statement: [MGA, languageContext, Malagasy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malagasy
Context triple: [MGA, languageContext, Malagasy]
  • A. Malagasy chosen
    Malagasy is an Austronesian language spoken predominantly in Madagascar and serves as a key marker of the island’s national identity and culture.
  • B. Betsileo Malagasy
    Betsileo Malagasy is a prominent regional variety of the Malagasy language spoken primarily by the Betsileo people in the central highlands of Madagascar.
  • C. Sakalava Malagasy
    Sakalava Malagasy is a regional variety of the Malagasy language spoken primarily by the Sakalava people of western Madagascar.
  • D. Betsimisaraka Malagasy
    Betsimisaraka Malagasy are a major ethnic group of Madagascar, traditionally inhabiting the island’s eastern coastal region and known for their seafaring, trading heritage, and distinct Malagasy dialect.
  • E. franc malgache
    Franc malgache is the French name for the former Malagasy franc, the historical currency of Madagascar before the adoption of the ariary.
  • 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_69e0c465ae7481908577b7209fdb2a77 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef538c5fbc8190a3316cf91f9516dc completed April 27, 2026, 12:16 p.m.
Created at: April 16, 2026, 6:35 p.m.