Triple

T4821559
Position Surface form Disambiguated ID Type / Status
Subject Mikołów E107720 entity
Predicate locatedNear P294 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: [Mikołów, locatedNear, Katowice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katowice
Context triple: [Mikołów, locatedNear, 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c99b46c8190b6fbcf9f98b9e993 completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c998a68c24819099abe74525830812 completed March 29, 2026, 9:24 p.m.
Created at: March 20, 2026, 1:24 p.m.