Triple

T6663362
Position Surface form Disambiguated ID Type / Status
Subject Ambrym E151530 entity
Predicate hasLanguage P15 FINISHED
Object Daakie language E608747 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: Daakie language | Statement: [Ambrym, hasLanguage, Daakie language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daakie language
Context triple: [Ambrym, hasLanguage, Daakie language]
  • A. Daakaka language chosen
    The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
  • B. Jangil language
    The Jangil language is an extinct and poorly documented Ongan language once spoken by the Jangil (Rutland Island) people of the Andaman Islands in India.
  • C. Modang language
    The Modang language is an Austronesian language spoken by the Modang people of Borneo, primarily in East Kalimantan, Indonesia.
  • D. Kaado language
    The Kaado language is a regional variety within the Songhay language family spoken by communities in parts of West Africa.
  • E. Amdang language
    The Amdang language is an Eastern Sudanic language spoken primarily in eastern Chad and western Sudan, closely associated with the Fur people and region.
  • 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_69c687f5fac48190a09e4838d9c6b45d completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b09a6fa88190ba8e454b9ad421a0 completed March 27, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f79cf0e48190a69294f3b13a8372 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:02 p.m.