Triple

T19096831
Position Surface form Disambiguated ID Type / Status
Subject Prístavný most E467427 entity
Predicate crosses P416 FINISHED
Object Dunaj 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: Dunaj | Statement: [Prístavný most, crosses, Dunaj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dunaj
Context triple: [Prístavný most, crosses, Dunaj]
  • A. Danube chosen
    The Danube is one of Europe's longest and most historically significant rivers, flowing from Germany to the Black Sea and passing through numerous Central and Eastern European countries.
  • B. Tisza
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • C. Alte Donau
    Alte Donau is a former branch of the Danube River in Vienna that now serves as a popular recreational lake for swimming, boating, and waterside leisure.
  • D. Donauquelle
    Donauquelle is the spring in Donaueschingen, Germany traditionally regarded as the source of the Danube River.
  • E. Dyje
    The Dyje is a major river in Central Europe that flows through the Czech Republic and Austria, forming part of their border and contributing significantly to the Morava River basin.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e369aeac81908913c21f4c234c8e completed April 20, 2026, 8:27 a.m.
Created at: April 10, 2026, 12:04 p.m.