Triple

T4797687
Position Surface form Disambiguated ID Type / Status
Subject Úslava E106751 entity
Predicate riverSystem P1009 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: [Úslava, riverSystem, Vltava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vltava
Context triple: [Úslava, riverSystem, 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. 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.
  • C. 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.
  • D. 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.
  • E. Váh River
    The Váh River is the longest river in Slovakia, flowing from the Tatra Mountains through much of the country before joining the Danube.
  • 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_69bd43f591c881909e5a532388b0f3f3 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6632708c8190b627d99363ab062c completed March 20, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c9fae9c8190bc231f3f83b82303 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:22 p.m.