Triple

T17620946
Position Surface form Disambiguated ID Type / Status
Subject Chukchi language E429706 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kerek language NE NERFINISHED

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: Kerek language | Statement: [Chukchi language, closelyRelatedTo, Kerek language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerek language
Context triple: [Chukchi language, closelyRelatedTo, Kerek language]
  • A. Kerek language chosen
    The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
  • B. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • C. Eket language
    The Eket language is a Niger-Congo language spoken by the Eket people of Akwa Ibom State in southeastern Nigeria.
  • D. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • E. Keka language
    Keka is an Austronesian language spoken on Rote Island in Indonesia, belonging to the Rote subgroup of languages.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d36074481909ee79e238841edf2 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.