Triple

T13593150
Position Surface form Disambiguated ID Type / Status
Subject Muoy-Bugle E324742 entity
Predicate hasAlternativeName P39 FINISHED
Object Buglé language E64360 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: Buglé language | Statement: [Muoy-Bugle, hasAlternativeName, Buglé language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buglé language
Context triple: [Muoy-Bugle, hasAlternativeName, Buglé language]
  • A. Nomatsiguenga language
    The Nomatsiguenga language is an Arawakan language spoken by the Nomatsiguenga people of Peru’s Amazon rainforest, closely associated with the broader Asháninka linguistic and cultural group.
  • B. Buglere language chosen
    The Buglere language is an indigenous Chibchan language spoken by the Buglere people of Panama and closely related to the Ngäbere language.
  • C. Batuley language
    The Batuley language is an Austronesian language spoken by a small community in Indonesia’s Aru Islands.
  • D. Belhare language
    The Belhare language is a Kiranti language of the Sino-Tibetan family spoken by the Belhare community in eastern Nepal.
  • E. Tête-de-Boule language
    Tête-de-Boule language, more commonly known as Atikamekw, is an Algonquian Indigenous language spoken by the Atikamekw people of Quebec, Canada.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7942c7f948190a62a8d2f69262ef3 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:49 p.m.