Triple

T17709762
Position Surface form Disambiguated ID Type / Status
Subject Sviatoshynsko–Brovarska line E441531 entity
Predicate hasStation P35 FINISHED
Object Universytet 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: Universytet | Statement: [Sviatoshynsko–Brovarska line, hasStation, Universytet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universytet
Context triple: [Sviatoshynsko–Brovarska line, hasStation, Universytet]
  • A. Universytet chosen
    Universytet is a central Kharkiv Metro station named for its proximity to major universities and academic institutions in the city.
  • B. Universitetet
    Universitetet is a railway station in Stockholm, Sweden, serving Stockholm University and located on the Roslagsbanan suburban rail line.
  • C. Universitate
    Universitate is a central Bucharest metro station located near the University of Bucharest and several major cultural and administrative landmarks.
  • D. Universitet
    Universitet is a Moscow Metro station serving the area around the Moscow State University campus on the Lenin Hills.
  • E. Universitat
    Universitat is a central Barcelona Metro station serving the busy Plaça de la Universitat area near the city's historic university.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4729a9a9c81908d65ff0bda12c961 completed April 19, 2026, 6:13 a.m.
Created at: April 10, 2026, 10:05 a.m.