Triple

T5331426
Position Surface form Disambiguated ID Type / Status
Subject Chagossians E123317 entity
Predicate ancestry P194 FINISHED
Object Malagasy E455431 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: Malagasy | Statement: [Chagossians, ancestry, Malagasy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malagasy
Context triple: [Chagossians, ancestry, Malagasy]
  • A. Malagasy
    Malagasy is an Austronesian language spoken predominantly in Madagascar and serves as a key marker of the island’s national identity and culture.
  • B. Malagasy people chosen
    The Malagasy people are the native inhabitants of Madagascar, known for their unique blend of Austronesian and African ancestry, languages, and cultural traditions.
  • C. 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.
  • D. Malaweg language
    The Malaweg language is an Austronesian language spoken primarily in the northern Philippines, particularly in parts of Cagayan province, by the Malaweg ethnic group.
  • 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 (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_69bd46477f9081909d242a327d749466 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85aab0308190990626cbc9da3e21 completed March 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18b75c388190955e4e31d71ffedb completed March 21, 2026, 10:16 p.m.
Created at: March 20, 2026, 2 p.m.