Triple

T16817595
Position Surface form Disambiguated ID Type / Status
Subject PSG Zlín E408793 entity
Predicate formerName P65 FINISHED
Object TJ Gottwaldov E420443 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: TJ Gottwaldov | Statement: [PSG Zlín, formerName, TJ Gottwaldov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TJ Gottwaldov
Context triple: [PSG Zlín, formerName, TJ Gottwaldov]
  • A. Mladá Boleslav
    Mladá Boleslav is a Czech city best known as an important industrial center and the headquarters of the Škoda Auto automobile manufacturer.
  • B. Gottwaldov chosen
    Gottwaldov is the former name (1949–1990) of the Czech industrial city now known as Zlín, historically associated with the Baťa shoe company.
  • C. Rousínov
    Rousínov is a small town in the South Moravian Region of the Czech Republic, known for its traditional furniture-making industry and proximity to the city of Brno.
  • D. Turnov
    Turnov is a historic town in the northern Czech Republic, known as a gateway to the Bohemian Paradise region and for its traditional gemstone cutting and jewelry-making.
  • E. Nymburk
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e30cf48190a61936ba0a49df24 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b297778c81909a2545c359739151 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.