Triple

T5130315
Position Surface form Disambiguated ID Type / Status
Subject Josef Gočár E115679 entity
Predicate placeOfDeath P21 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: [Josef Gočár, placeOfDeath, Jičín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jičín
Context triple: [Josef Gočár, placeOfDeath, 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. 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. Kolín
    Kolín is a historic industrial town and important transport hub on the Elbe River in the Central Bohemian Region of the Czech Republic.
  • E. 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.
  • 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_69bd444426bc819099ccd23f141e22aa completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7827c764819086da3b79f2020224 completed March 20, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe8ba08f88190a0b10b7a0a05b98c completed March 22, 2026, 1:03 p.m.
Created at: March 20, 2026, 1:42 p.m.