Triple

T19172616
Position Surface form Disambiguated ID Type / Status
Subject Betul district E469361 entity
Predicate majorLanguage P207 FINISHED
Object Korku E491308 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: Korku | Statement: [Betul district, majorLanguage, Korku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korku
Context triple: [Betul district, majorLanguage, Korku]
  • A. Korku chosen
    Korku is an indigenous tribal language of central India, primarily spoken by the Korku people in parts of Maharashtra and neighboring states.
  • B. Horki
    Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
  • C. Osokorky
    Osokorky is a metro station on the Kyiv Metro system in Ukraine, serving the residential district of the same name on the city's left bank.
  • D. Kökeqota
    Kökeqota is a historic city in what is now Hohhot, Inner Mongolia, that served as the principal political and administrative center of the Northern Yuan dynasty after the fall of the Yuan in China.
  • E. Kök
    Kök is a Turkish surname most notably borne by Mustafa Verşan Kök, a Turkish academic and university administrator.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f16544948190bd10ca7804dd27a5 completed April 20, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a06f8ac3304819091fa43ec3f7573b6 completed May 15, 2026, 10:42 a.m.
Created at: April 10, 2026, 12:06 p.m.