Triple

T8945958
Position Surface form Disambiguated ID Type / Status
Subject Kattowitz E213221 entity
Predicate hasAlternativeName P39 FINISHED
Object Katowice E32146 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: Katowice | Statement: [Kattowitz, hasAlternativeName, Katowice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katowice
Context triple: [Kattowitz, hasAlternativeName, Katowice]
  • A. Katowice chosen
    Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
  • B. Wrocław
    Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
  • C. Gliwice
    Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
  • D. Opole Silesia
    Opole Silesia is a historical and cultural region in southwestern Poland, known for its mixed Polish-German heritage and centered around the city of Opole.
  • E. Dąbrowa Górnicza
    Dąbrowa Górnicza is an industrial city in southern Poland’s Silesian Voivodeship, known for its heavy industry, mining heritage, and proximity to the unique Błędów Desert.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66dd00c481908ff20fd66c1954cc completed April 1, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dbc697388190b384c7ed9e6a65dc completed April 10, 2026, 11:15 a.m.
Created at: March 30, 2026, 6:59 p.m.