Triple

T9189749
Position Surface form Disambiguated ID Type / Status
Subject Kurzętnik E220550 entity
Predicate hasOfficialName P66 FINISHED
Object Kurzętnik E220550 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: Kurzętnik | Statement: [Kurzętnik, hasOfficialName, Kurzętnik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kurzętnik
Context triple: [Kurzętnik, hasOfficialName, Kurzętnik]
  • A. Kurzętnik chosen
    Kurzętnik is a village in northern Poland known for its historical character and location within the picturesque Warmian-Masurian region.
  • B. Gajowniczek
    Gajowniczek is a Polish surname most notably borne by Franciszek Gajowniczek, the Auschwitz prisoner for whom Saint Maximilian Kolbe volunteered to die.
  • C. Ryszka
    Ryszka is a minor river or stream in Poland that serves as a tributary of the Wda River.
  • D. Czarny Groń
    Czarny Groń is a mountain peak in southern Poland, located in the Maków Beskids range and known for its hiking and skiing opportunities.
  • E. Sokółka
    Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
  • 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_69ca83e6d77c81909862b7afef56b1bf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5bd8c5c81909d0cdbcd7410fcee completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c272f508190aade1769c88cf16d completed April 4, 2026, 12:32 a.m.
Created at: March 30, 2026, 7:24 p.m.