Triple

T4236837
Position Surface form Disambiguated ID Type / Status
Subject Albrecht von Wallenstein E94713 entity
Predicate burialPlace P196 FINISHED
Object Mladá Boleslav E226300 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: Mladá Boleslav | Statement: [Albrecht von Wallenstein, burialPlace, Mladá Boleslav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mladá Boleslav
Context triple: [Albrecht von Wallenstein, burialPlace, Mladá Boleslav]
  • A. Mladá Boleslav chosen
    Mladá Boleslav is a Czech city best known as an important industrial center and the headquarters of the Škoda Auto automobile manufacturer.
  • B. Nymburk
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • C. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • D. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • E. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • 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_69b5d05f55f48190b671830e173ef2ba completed March 14, 2026, 9:17 p.m.
Created at: March 12, 2026, 11:05 p.m.