Triple

T10586585
Position Surface form Disambiguated ID Type / Status
Subject Toposa language E249869 entity
Predicate closelyRelatedTo P37 FINISHED
Object Teso 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: Teso language | Statement: [Toposa language, closelyRelatedTo, Teso language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teso language
Context triple: [Toposa language, closelyRelatedTo, Teso 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. Tehueco language
    The Tehueco language is an extinct indigenous language of northern Mexico that belonged to the Taracahitic branch of the Uto-Aztecan language family.
  • C. Toposa language
    The Toposa language is an Eastern Nilotic language spoken primarily by the Toposa people of South Sudan and neighboring regions.
  • D. 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.
  • E. Teke-Kukuya language
    The Teke-Kukuya language is a Bantu language spoken by the Teke-Kukuya people in the Republic of the Congo and neighboring regions of Central Africa.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5276b0ae48190b2935230363239e0 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b8b1b708190865e428128f98720 completed April 10, 2026, 7:12 p.m.
Created at: April 6, 2026, 12:39 p.m.