Triple

T17717250
Position Surface form Disambiguated ID Type / Status
Subject Karlovy Vary District E442230 entity
Predicate containsRiver P165 FINISHED
Object Teplá 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: Teplá | Statement: [Karlovy Vary District, containsRiver, Teplá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teplá
Context triple: [Karlovy Vary District, containsRiver, Teplá]
  • A. Teplá chosen
    Teplá is a river in the western Czech Republic that flows through the spa city of Karlovy Vary before joining the Ohře River.
  • B. Dolní Teplice
    Dolní Teplice is a village and administrative part of the town of Teplice nad Metují in the Hradec Králové Region of the Czech Republic.
  • C. Trenčianska Teplá
    Trenčianska Teplá is a village and municipality in western Slovakia known for its location near the spa town of Trenčianske Teplice and the regional center Trenčín.
  • D. Liptovská Teplička
    Liptovská Teplička is a traditional mountain village in northern Slovakia, known for its distinctive terraced potato fields and well-preserved folk architecture.
  • E. Rajecké Teplice
    Rajecké Teplice is a Slovak spa town renowned for its thermal springs and wellness tourism.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47481663c8190a1110385e5596ab0 completed April 19, 2026, 6:21 a.m.
Created at: April 10, 2026, 10:06 a.m.