Triple

T1456480
Position Surface form Disambiguated ID Type / Status
Subject Czechs E31411 entity
Predicate populationCenter P2106 FINISHED
Object Ostrava E32147 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: Ostrava | Statement: [Czechs, populationCenter, Ostrava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ostrava
Context triple: [Czechs, populationCenter, Ostrava]
  • A. Ostrava chosen
    Ostrava is a major industrial and cultural city in the northeastern Czech Republic, near the borders with Poland and Slovakia.
  • B. Opava
    Opava is a historic city in the Czech Republic’s Silesian region, known as a former political and cultural center of Silesia.
  • C. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • D. Brno
    Brno is the second-largest city in the Czech Republic, known as a major cultural, educational, and industrial center in the historical region of Moravia.
  • E. Olomouc
    Olomouc is a historic city in the eastern Czech Republic known for its well-preserved old town, Baroque architecture, and UNESCO-listed Holy Trinity Column.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c598b30c8190b87207adf608b89a completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3b07b688190a0c90796da21c4d5 completed March 8, 2026, 10:09 p.m.
Created at: March 1, 2026, 8 p.m.