Triple

T12063045
Position Surface form Disambiguated ID Type / Status
Subject Opole Voivodeship E287221 entity
Predicate containsCity P294 FINISHED
Object Kędzierzyn-Koźle E692052 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: Kędzierzyn-Koźle | Statement: [Opole Voivodeship, containsCity, Kędzierzyn-Koźle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kędzierzyn-Koźle
Context triple: [Opole Voivodeship, containsCity, Kędzierzyn-Koźle]
  • A. Kędzierzyn-Koźle chosen
    Kędzierzyn-Koźle is a town in southern Poland known as an important industrial and river port center on the Oder River.
  • B. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • C. Kluczbork
    Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
  • D. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • E. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043f82248190b05692aa0dc178a8 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5b2fb308190ab041a9cfe39087c completed May 8, 2026, 12:23 p.m.
Created at: April 8, 2026, 9:48 p.m.