Triple

T20783973
Position Surface form Disambiguated ID Type / Status
Subject Esztergom region E511579 entity
Predicate crossBorderConnection P41237 FINISHED
Object Mária Valéria Bridge 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: Mária Valéria Bridge | Statement: [Esztergom region, crossBorderConnection, Mária Valéria Bridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mária Valéria Bridge
Context triple: [Esztergom region, crossBorderConnection, Mária Valéria Bridge]
  • A. Mária Valéria Bridge chosen
    Mária Valéria Bridge is a historic road and pedestrian bridge over the Danube River that connects the Hungarian city of Esztergom with Štúrovo in Slovakia.
  • B. Megyeri Bridge
    Megyeri Bridge is a modern cable-stayed bridge over the Danube River in Budapest, Hungary, serving as a key northern bypass for the city’s ring road system.
  • C. Tiszavirág Bridge
    Tiszavirág Bridge is a distinctive pedestrian and cyclist bridge in Szolnok, Hungary, known for its elegant, dragonfly-inspired design spanning the Tisza River.
  • D. Torgovy Bridge
    Torgovy Bridge is a historic pedestrian bridge spanning the Griboyedov Canal in Saint Petersburg, Russia.
  • E. Tyrš Bridge
    Tyrš Bridge is a notable road and pedestrian bridge spanning the Elbe River in the Czech city of Děčín.
  • 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_69e0b4cac7a48190a715cb3d545df2b4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c28a4584819084d2d02febe47001 completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:38 p.m.