Triple

T20797641
Position Surface form Disambiguated ID Type / Status
Subject Karo Regency E511952 entity
Predicate contains P35 FINISHED
Object Berastagi 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: Berastagi | Statement: [Karo Regency, contains, Berastagi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berastagi
Context triple: [Karo Regency, contains, Berastagi]
  • A. Berastagi chosen
    Berastagi is a cool highland town in North Sumatra, Indonesia, known for its volcanoes, fruit and flower markets, and scenic views, making it a popular weekend getaway from Medan.
  • B. Bastan
    Bastan is a family of turboprop aircraft engines developed by Turbomeca and used on several regional and military transport aircraft.
  • C. Bastam
    Bastam is an ancient town in Iran renowned for its significant Islamic architectural and Sufi heritage, including monuments from the Seljuk and Ilkhanid periods.
  • D. Bara
    Bara is a town in Pakistan’s Khyber District, known as a key settlement in the Khyber Pass region with strategic and commercial significance.
  • E. Bara
    Bara is a town in central Sudan known as an agricultural and trading center in North Kordofan State.
  • 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_69e0b4cc69f481908e98751e697b9df4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2ae2c4c819087f620df31dc1aba completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:39 p.m.