Triple

T23338580
Position Surface form Disambiguated ID Type / Status
Subject Nirkh District E591670 entity
Predicate provinceCapital P16248 FINISHED
Object Maidan Shahr 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: Maidan Shahr | Statement: [Nirkh District, provinceCapital, Maidan Shahr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maidan Shahr
Context triple: [Nirkh District, provinceCapital, Maidan Shahr]
  • A. Maidan Shahr chosen
    Maidan Shahr is a town in central Afghanistan that serves as the administrative and commercial hub of Wardak Province.
  • B. Leninabad
    Leninabad was the Soviet-era name of the city now known as Khujand, a major historical and industrial center in northern Tajikistan.
  • C. Alma-Atinskaya
    Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
  • D. Kairana
    Kairana is a town and parliamentary constituency in the Shamli district of Uttar Pradesh, India, known for its agrarian population and political significance in north Indian politics.
  • E. Qaisar District
    Qaisar District is an administrative district located in Faryab Province in northern Afghanistan.
  • 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_69e25d20156c81908c5c53195bd9c738 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1983099188190a2e05cf81d62a641 completed April 29, 2026, 5:33 a.m.
Created at: April 17, 2026, 5:17 p.m.