Triple

T20864634
Position Surface form Disambiguated ID Type / Status
Subject České středohoří E513719 entity
Predicate near P350 FINISHED
Object Teplice 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: Teplice | Statement: [České středohoří, near, Teplice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teplice
Context triple: [České středohoří, near, Teplice]
  • A. Teplice chosen
    Teplice is a historic spa city in the north of the Czech Republic, renowned for its thermal springs and long tradition of balneotherapy.
  • B. Teplice nad Metují
    Teplice nad Metují is a small town in northeastern Czech Republic known as a gateway to the Adršpach-Teplice rock formations and scenic sandstone landscapes.
  • C. Žatec
    Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
  • D. Opava
    Opava is a historic city in the Czech Republic’s Silesian region, known as a former political and cultural center of Silesia.
  • E. 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.
  • 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c45e51f08190ac1ff59280ad741b completed April 21, 2026, 12:27 a.m.
Created at: April 16, 2026, 12:44 p.m.