Triple

T3055467
Position Surface form Disambiguated ID Type / Status
Subject Dinka language E60468 entity
Predicate closelyRelatedTo P37 FINISHED
Object Atuot language E247235 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: Atuot language | Statement: [Dinka language, closelyRelatedTo, Atuot language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atuot language
Context triple: [Dinka language, closelyRelatedTo, Atuot language]
  • A. Atuot language chosen
    The Atuot language is a Western Nilotic language spoken by the Atuot people of South Sudan, closely related to Nuer and Dinka.
  • B. Attié language
    The Attié language is a Niger-Congo language spoken primarily by the Attié people of southern Côte d'Ivoire.
  • C. Tai Aiton language
    The Tai Aiton language is a Southwestern Tai language spoken by the Tai Aiton ethnic community in northeastern India, particularly in Assam.
  • D. Opata language
    The Opata language is an extinct Uto-Aztecan language once spoken by the Opata people of northern Mexico, particularly in the present-day state of Sonora.
  • E. Avokaya language
    The Avokaya language is a Central Sudanic language spoken primarily by the Avokaya people in parts of South Sudan and the Democratic Republic of the Congo.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9bf6b9948190bc957bfd1579c471 completed March 8, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef03425c8190a44486ab563c210f completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 3:02 p.m.