Triple

T11424237
Position Surface form Disambiguated ID Type / Status
Subject Moru–Madi languages E270703 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Keliko language E262850 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: Keliko language | Statement: [Moru–Madi languages, hasMemberLanguage, Keliko language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keliko language
Context triple: [Moru–Madi languages, hasMemberLanguage, Keliko language]
  • A. Keliko language chosen
    The Keliko language is a Central Sudanic language spoken primarily by the Keliko people of South Sudan and the Democratic Republic of the Congo.
  • B. Kayeli language
    The Kayeli language is an Austronesian language once spoken on Buru Island in Indonesia, now critically endangered or possibly extinct.
  • C. Jakaltek language
    The Jakaltek language is a Mayan language spoken primarily by the Jakaltek (Popti’) people of northwestern Guatemala and parts of southern Mexico.
  • D. Kioko language
    The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
  • E. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806be9c2c819084da13101cbb6c81 completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b8b553808190bf8b40d9b03e12b7 completed April 20, 2026, 5:25 a.m.
Created at: April 8, 2026, 9:35 p.m.