Triple

T20589329
Position Surface form Disambiguated ID Type / Status
Subject Julie Anne Legate E505871 entity
Predicate researchInterest P3 FINISHED
Object Malagasy 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: Malagasy language | Statement: [Julie Anne Legate, researchInterest, Malagasy language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malagasy language
Context triple: [Julie Anne Legate, researchInterest, Malagasy language]
  • 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. Comorian language
    Comorian is a Bantu language spoken primarily in the Comoros Islands, closely related to Swahili and used in several regional varieties.
  • E. Tsonga language
    The Tsonga language is a Bantu language spoken primarily in southern Africa, especially in Mozambique, South Africa, Eswatini, and Zimbabwe.
  • 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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a979e4a48190a948165fb0f3b265 completed April 20, 2026, 10:32 p.m.
Created at: April 16, 2026, 11:40 a.m.