Triple

T23305119
Position Surface form Disambiguated ID Type / Status
Subject Prague 9 E590414 entity
Predicate contains P35 FINISHED
Object Vysočany E1222073 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: Vysočany | Statement: [Prague 9, contains, Vysočany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vysočany
Context triple: [Prague 9, contains, Vysočany]
  • A. Vysočany chosen
    Vysočany is a district in the northeastern part of Prague, Czech Republic, known for its mix of residential areas, industrial heritage, and modern commercial development.
  • B. Vranov nad Topľou
    Vranov nad Topľou is a town in eastern Slovakia known as a local administrative and cultural center in the Prešov Region.
  • C. Trebišov
    Trebišov is a town in eastern Slovakia known as an administrative and cultural center of the Trebišov District.
  • D. Hlboké nad Váhom
    Hlboké nad Váhom is a village and municipality in northern Slovakia, situated in the Bytča District of the Žilina Region.
  • E. Ružomberok
    Ružomberok is a town in northern Slovakia known for its location in the Liptov region and its historical and cultural significance.
  • 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_69e25d1c0ecc8190a355aa229f06d0e0 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19725b248819089e61efb82e3440f completed April 29, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4c9934ec819094ebbe6e61d18ab7 completed May 19, 2026, 11:42 a.m.
Created at: April 17, 2026, 5:04 p.m.