Triple

T8968013
Position Surface form Disambiguated ID Type / Status
Subject Kralupy nad Vltavou E214187 entity
Predicate locatedOnRiver P165 FINISHED
Object Vltava E108852 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: Vltava | Statement: [Kralupy nad Vltavou, locatedOnRiver, Vltava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vltava
Context triple: [Kralupy nad Vltavou, locatedOnRiver, Vltava]
  • A. Vltava River chosen
    The Vltava River is the longest river in the Czech Republic, flowing through the capital city of Prague and serving as a central feature of its landscape and history.
  • B. Svitava River
    The Svitava River is a significant river in the eastern Czech Republic that flows through cities such as Brno before joining the Svratka River.
  • C. Havel River
    The Havel River is a major waterway in northeastern Germany that flows through Berlin and Brandenburg, connecting numerous lakes and serving as an important route for transport and recreation.
  • D. Hron River
    The Hron River is a major river in central Slovakia that flows through mountainous regions including the Low Tatras before joining the Danube.
  • E. Sázava River
    The Sázava River is a scenic tributary of the Vltava in the Czech Republic, known for its picturesque valleys, historic sites, and popularity for canoeing and recreation.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6764aca48190a5e472d1b6841886 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc95cbc4c8190a3ac582f735eeb35 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:01 p.m.