Triple

T20765313
Position Surface form Disambiguated ID Type / Status
Subject Southern Ethiopia E511079 entity
Predicate hasLanguage P15 FINISHED
Object Hadiyya 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: Hadiyya language | Statement: [Southern Ethiopia, hasLanguage, Hadiyya language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hadiyya language
Context triple: [Southern Ethiopia, hasLanguage, Hadiyya language]
  • A. Hadiyya language chosen
    The Hadiyya language is a Highland East Cushitic language spoken by the Hadiya people of southern Ethiopia.
  • B. Khwarshi language
    The Khwarshi language is a Northeast Caucasian (Nakh-Daghestanian) language spoken by a small ethnic group in Dagestan, Russia, known for its complex phonology and rich case system.
  • C. Lundayeh language
    The Lundayeh language is an Austronesian language spoken by the Lundayeh (Lun Bawang) people of northern Borneo, primarily in parts of Malaysia and Indonesia.
  • D. Adiyan language
    The Adiyan language is a lesser-known Dravidian language spoken by the Adiyan tribal community, primarily in parts of southern India.
  • E. Dida language
    Dida language is a Niger-Congo language spoken primarily in Côte d'Ivoire, belonging to the Kru branch and known for its tonal and dialectal diversity.
  • 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_69e0b4ca01148190ac018e57e0cab46f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c24bde0c8190b46986b89bf2e037 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:36 p.m.