Triple

T2233669
Position Surface form Disambiguated ID Type / Status
Subject Teso language E49228 entity
Predicate alternateName P39 FINISHED
Object Ateso language E49228 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: Ateso language | Statement: [Teso language, alternateName, Ateso language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ateso language
Context triple: [Teso language, alternateName, Ateso language]
  • A. Teso language chosen
    Teso language is an Eastern Nilotic language spoken primarily by the Iteso people in eastern Uganda and western Kenya.
  • B. Arosi language
    The Arosi language is an Oceanic language spoken primarily on Makira Island in the Solomon Islands.
  • C. Patamona language
    The Patamona language is an indigenous Cariban language spoken by the Patamona people of the Guiana Highlands in Guyana and northern Brazil.
  • D. Amuesha language
    The Amuesha language, also known as Yanesha', is an Arawakan language spoken by the Yanesha' people of the central Peruvian Amazon.
  • E. Tonsea language
    Tonsea is an Austronesian language spoken by the Tonsea people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0913f1c8190ac9cfeb0f1c84a76 completed March 7, 2026, 6:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b020e308190a6d5a50a8e808aba completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:47 p.m.