Triple

T13195623
Position Surface form Disambiguated ID Type / Status
Subject Machiguenga E314102 entity
Predicate alternativeName P39 FINISHED
Object Matsiguenka E505445 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: Matsiguenka | Statement: [Machiguenga, alternativeName, Matsiguenka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matsiguenka
Context triple: [Machiguenga, alternativeName, Matsiguenka]
  • A. Matsigenka chosen
    The Matsigenka are an Indigenous people of the Peruvian Amazon known for their forest-based subsistence lifestyle, distinct language, and rich shamanic and cosmological traditions.
  • B. Musanze
    Musanze is a major town in northern Rwanda that serves as the primary gateway for tourists visiting Volcanoes National Park and its mountain gorillas.
  • C. Kasangati
    Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
  • D. Mutengene
    Mutengene is a town in southwestern Cameroon known as a key road junction linking the coastal city of Limbe with Buea and other inland areas.
  • E. Masisi
    Masisi is a town in the eastern Democratic Republic of the Congo, situated in the conflict-affected, mineral-rich highlands of North Kivu Province.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c626058819086f604b11af2d4eb completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff177ba88190afb2043cc157248d completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 9:16 p.m.