Triple

T21982155
Position Surface form Disambiguated ID Type / Status
Subject Ngaju Dayak E542867 entity
Predicate languageSpoken P151 FINISHED
Object Ngaju 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: Ngaju language | Statement: [Ngaju Dayak, languageSpoken, Ngaju language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngaju language
Context triple: [Ngaju Dayak, languageSpoken, Ngaju language]
  • A. Ngaju language chosen
    The Ngaju language is an Austronesian language spoken primarily by the Ngaju Dayak people of central Kalimantan in Indonesian Borneo.
  • B. Aja language
    The Aja language is a Gbe language of the Niger-Congo family spoken primarily in parts of Benin and Togo.
  • C. Wauja language
    The Wauja language is an indigenous Arawakan language spoken by the Wauja people of Brazil’s Upper Xingu region in the Amazon.
  • D. Parji language
    The Parji language is a lesser-known Dravidian language spoken primarily by tribal communities in central India, particularly in parts of Chhattisgarh and Odisha.
  • E. Tagakaulo language
    Tagakaulo language is an Austronesian language spoken by the Tagakaulo people of Mindanao in the southern Philippines.
  • 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1248de3688190a8d24cc8458851f2 completed April 28, 2026, 9:20 p.m.
Created at: April 16, 2026, 8:04 p.m.