Triple

T6220810
Position Surface form Disambiguated ID Type / Status
Subject Dinka people E139107 entity
Predicate language P15 FINISHED
Object Dinka language E60468 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: Dinka language | Statement: [Dinka people, language, Dinka language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinka language
Context triple: [Dinka people, language, Dinka language]
  • A. Dinka language chosen
    The Dinka language is a Western Nilotic language spoken primarily by the Dinka people of South Sudan, known for its complex system of tones and vowel lengths.
  • B. Nuer language
    Nuer language is a Western Nilotic language spoken primarily by the Nuer people of South Sudan and western Ethiopia.
  • C. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • D. Dagbani language
    Dagbani is a major Gur language of northern Ghana, spoken primarily by the Dagomba people and used widely in education, media, and regional communication.
  • E. Nilotic languages
    Nilotic languages are a branch of the Nilo-Saharan language family spoken primarily along the Nile Valley and surrounding regions of East and Central Africa by various pastoralist and agricultural communities.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bcc2348190806ed8c98bdfbf3e completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dc349b481909ce369a82fa96412 completed March 24, 2026, 4:06 a.m.
Created at: March 22, 2026, 4:21 p.m.