Triple

T18598732
Position Surface form Disambiguated ID Type / Status
Subject Biak people E454564 entity
Predicate language P15 FINISHED
Object Biak 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: Biak language | Statement: [Biak people, language, Biak language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biak language
Context triple: [Biak people, language, Biak language]
  • A. Biak language chosen
    The Biak language is an Austronesian language spoken primarily on Biak Island and nearby areas in Papua, Indonesia, known for its complex verbal morphology and rich oral traditions.
  • B. Talaud language
    The Talaud language is an Austronesian language spoken by the indigenous population of the Talaud Islands in North Sulawesi, Indonesia.
  • C. Tanimbar languages
    The Tanimbar languages are a subgroup of Austronesian languages spoken primarily in the Tanimbar Islands of eastern Indonesia.
  • D. Tidore language
    The Tidore language is a North Halmahera language of eastern Indonesia, spoken primarily on Tidore Island and nearby areas in North Maluku.
  • E. Betawi language
    Betawi language is an Austronesian language variety spoken primarily in Jakarta, Indonesia, known for blending Malay with influences from Javanese, Sundanese, Chinese, Arabic, and Dutch.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5474f1d548190b74408eabd396344 completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:45 a.m.