Triple

T19302587
Position Surface form Disambiguated ID Type / Status
Subject VŠE E482738 entity
Predicate shortName P43 FINISHED
Object VŠE 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: VŠE | Statement: [VŠE, shortName, VŠE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VŠE
Context triple: [VŠE, shortName, VŠE]
  • A. VŠE chosen
    VŠE is the commonly used abbreviation for the University of Economics in Prague, a leading Czech institution specializing in economics and business studies.
  • B. VSE
    VSE is the commonly used abbreviation for the Vine Street Expressway, a major freeway segment of Interstate 676 in Philadelphia, Pennsylvania.
  • C. VUT
    VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
  • D. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • E.
    VŽ is the vehicle registration code used for the town of Ludbreg in Croatia.
  • 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc8add788190aed98bcbad518808 completed April 20, 2026, 10:14 a.m.
Created at: April 10, 2026, 1:31 p.m.