Triple

T4139072
Position Surface form Disambiguated ID Type / Status
Subject Hazara E89227 entity
Predicate hasTown P847 FINISHED
Object Havelian E271514 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: Havelian | Statement: [Hazara, hasTown, Havelian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havelian
Context triple: [Hazara, hasTown, Havelian]
  • A. Havelian chosen
    Havelian is a town in Pakistan’s Khyber Pakhtunkhwa province, known as a local commercial center and a key junction on the Karakoram Highway.
  • B. Havel
    The Havel is a river in northeastern Germany that flows through Berlin and Brandenburg before joining the Elbe.
  • C. Havlíček
    Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
  • D. Orlovsky
    Orlovsky is a surname most notably associated with Peter Orlovsky, the American poet and longtime partner of Beat Generation writer Allen Ginsberg.
  • E. Czech New Wave
    Czech New Wave was a 1960s Czechoslovak film movement known for its innovative, humanistic, and often politically subversive cinema that blended realism with dark humor and formal experimentation.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02485a788190ba6ee769e663b2d3 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576c9f8a081908c2910ac475e4974 completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:43 p.m.