Triple

T13347514
Position Surface form Disambiguated ID Type / Status
Subject powiat suski E317990 entity
Predicate hasSettlement P1068 FINISHED
Object Toporzysko E1035043 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: Toporzysko | Statement: [powiat suski, hasSettlement, Toporzysko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toporzysko
Context triple: [powiat suski, hasSettlement, Toporzysko]
  • A. Toporzysko chosen
    Toporzysko is a village in southern Poland located within the administrative district of Gmina Jordanów.
  • B. Prószków
    Prószków is a small town in southwestern Poland known for its historical architecture and location near the regional capital, Opole.
  • C. Pużak
    Pużak is a Polish surname most notably associated with Kazimierz Pużak, a prominent socialist politician and resistance activist in 20th-century Poland.
  • D. Czeladź
    Czeladź is a historic industrial town in southern Poland, located in the Silesian metropolitan area near Katowice.
  • E. Turbacz
    Turbacz is the highest peak of Poland’s Gorce Mountains, known for its extensive forested slopes and panoramic views, and as a popular destination for hikers.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8b28e48190a23194e03a74b41b completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f726738ea08190b0b7634b29f5d94e completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:31 p.m.