Triple

T17620897
Position Surface form Disambiguated ID Type / Status
Subject Льыгъоравэтлььэт E429705 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kerek language
The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
 E1279458 NE FINISHED

How this triple was built (4 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: [Льыгъоравэтлььэт, closelyRelatedTo, Kerek language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kerek language
Context triple: [Льыгъоравэтлььэт, closelyRelatedTo, Kerek language]
  • A. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • B. Eket language
    The Eket language is a Niger-Congo language spoken by the Eket people of Akwa Ibom State in southeastern Nigeria.
  • C. 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.
  • D. Keka language
    Keka is an Austronesian language spoken on Rote Island in Indonesia, belonging to the Rote subgroup of languages.
  • E. Kitharaka language
    The Kitharaka language is a Bantu language spoken by the Tharaka people of Kenya, closely related to neighboring Kamba and Meru varieties.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kerek language
Triple: [Льыгъоравэтлььэт, closelyRelatedTo, Kerek language]
Generated description
The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kerek language
Target entity description: The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
  • A. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • B. Eket language
    The Eket language is a Niger-Congo language spoken by the Eket people of Akwa Ibom State in southeastern Nigeria.
  • C. 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.
  • D. Keka language
    Keka is an Austronesian language spoken on Rote Island in Indonesia, belonging to the Rote subgroup of languages.
  • E. Kitharaka language
    The Kitharaka language is a Bantu language spoken by the Tharaka people of Kenya, closely related to neighboring Kamba and Meru varieties.
  • F. None of above. chosen

Provenance (5 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.
NED1 Entity disambiguation (via context triple) batch_6a020a9553f08190a4cd8fea76f016df completed May 11, 2026, 4:57 p.m.
NEDg Description generation batch_6a020bec249c81909148778f348fb1b4 completed May 11, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_6a020ce0cc0081909e9e90b9067e3f01 completed May 11, 2026, 5:07 p.m.
Created at: April 10, 2026, 5:51 a.m.