Triple

T4236841
Position Surface form Disambiguated ID Type / Status
Subject Albrecht von Wallenstein E94713 entity
Predicate residence P75 FINISHED
Object Jičín E305393 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: Jičín | Statement: [Albrecht von Wallenstein, residence, Jičín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jičín
Context triple: [Albrecht von Wallenstein, residence, Jičín]
  • A. Jičín chosen
    Jičín is a historic town in the Czech Republic known for its well-preserved medieval center and association with the fairy-tale character Rumcajs.
  • B. Nymburk
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • C. Kolín
    Kolín is a historic industrial town and important transport hub on the Elbe River in the Central Bohemian Region of the Czech Republic.
  • D. Havlíčkův Brod
    Havlíčkův Brod is a historic town in the Vysočina Region of the Czech Republic, situated on the Sázava River and known for its medieval center and long-standing brewing tradition.
  • E. Jihlava
    Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e7422a88190955f5f4347fa80d2 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db7cdcdc81909f7b42bade322c67 completed March 14, 2026, 10:04 p.m.
Created at: March 12, 2026, 11:05 p.m.