Triple

T7103178
Position Surface form Disambiguated ID Type / Status
Subject Sumba people E165509 entity
Predicate language P15 FINISHED
Object Mamboru language E637586 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: Mamboru language | Statement: [Sumba people, language, Mamboru language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamboru language
Context triple: [Sumba people, language, Mamboru language]
  • A. Mamboru language chosen
    The Mamboru language is an Austronesian language spoken by a small community on Sumba Island in eastern Indonesia.
  • B. Maasai language
    Maasai language is an Eastern Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania, known for its rich oral tradition and distinctive phonology.
  • C. Moghamo language
    The Moghamo language is a Bantu-related Grassfields language spoken by the Moghamo people in the Northwest Region of Cameroon.
  • D. Kambaata language
    The Kambaata language is a Cushitic language of the Afroasiatic family spoken primarily by the Kambaata people in southern Ethiopia.
  • E. Kamba language
    Kamba language is a Bantu language spoken primarily by the Kamba people of Kenya, known for its rich oral traditions and close linguistic ties to other Central Kenya Bantu languages.
  • 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_69c6887fcddc8190a5d58908f6dee590 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e58a0a2c819088e0c8874fb4491f completed March 27, 2026, 8:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79cad60788190bb2b17d1c3f8e1cc completed March 28, 2026, 9:17 a.m.
Created at: March 27, 2026, 2:42 p.m.