Triple

T10483064
Position Surface form Disambiguated ID Type / Status
Subject Kalenjin E247219 entity
Predicate hasDialect P4251 FINISHED
Object Terik E247226 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: Terik | Statement: [Kalenjin, hasDialect, Terik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terik
Context triple: [Kalenjin, hasDialect, Terik]
  • A. Terik chosen
    Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
  • B. The Turim
    The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
  • C. Terioki
    Terioki was the former name of the Finnish coastal town now known as Zelenogorsk, a resort area near Saint Petersburg on the Gulf of Finland.
  • D. Teron
    Teron is one of the traditional clans of the Karbi people, an indigenous ethnic group primarily inhabiting the Karbi Anglong region of Assam in Northeast India.
  • E. Teisen
    Teisen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green spaces, and convenient access to public transportation.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509678ac88190984f18a2162e2dcf completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a03c647c81909521fee4a66ec8ac completed April 10, 2026, 7:01 a.m.
Created at: April 6, 2026, 12:22 p.m.