Triple

T1886277
Position Surface form Disambiguated ID Type / Status
Subject Škoda E39971 entity
Predicate foundingLocation P40 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: [Škoda, foundingLocation, Mladá Boleslav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mladá Boleslav
Context triple: [Škoda, foundingLocation, 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb12032c881909cd93e3601906f48 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69af652eb8ac81908ba29989c1197daf completed March 10, 2026, 12:26 a.m.
Created at: March 4, 2026, 7:34 p.m.