Triple

T3533587
Position Surface form Disambiguated ID Type / Status
Subject Meissen E74716 entity
Predicate hasTwinTown P919 FINISHED
Object Mělník E231915 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: Mělník | Statement: [Meissen, hasTwinTown, Mělník]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mělník
Context triple: [Meissen, hasTwinTown, Mělník]
  • A. Mělník chosen
    Mělník is a historic Czech town north of Prague, known for its wine production and its location at the confluence of the Elbe and Vltava rivers.
  • B. Broumov
    Broumov is a historic town in northeastern Bohemia, Czech Republic, known for its Benedictine monastery and proximity to the Broumov Walls sandstone rock formations.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Říčany
    Říčany is a town in the Czech Republic, located just southeast of Prague and known as a popular residential and commuter suburb with historical roots.
  • E. Karviná
    Karviná is an industrial city in the Moravian-Silesian Region of the Czech Republic, historically part of Cieszyn Silesia and known for its coal mining heritage.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9b945481909867d44b810e8b1f completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb87c3748190bce62e86fcdfa380 completed March 13, 2026, 7:23 a.m.
Created at: March 8, 2026, 3:19 p.m.