Triple

T3160682
Position Surface form Disambiguated ID Type / Status
Subject Kasprowy Wierch E66093 entity
Predicate nearestTown P350 FINISHED
Object Zakopane E24091 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: Zakopane | Statement: [Kasprowy Wierch, nearestTown, Zakopane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zakopane
Context triple: [Kasprowy Wierch, nearestTown, Zakopane]
  • A. Zakopane chosen
    Zakopane is a popular resort town in southern Poland, known as the country's "winter capital" and a gateway to the Tatra Mountains.
  • B. Karpacz
    Karpacz is a popular mountain resort town in southwestern Poland, known for skiing, hiking, and its location at the foot of Śnieżka in the Sudetes.
  • C. Jelenia Góra
    Jelenia Góra is a historic city in southwestern Poland, known for its picturesque setting in the Karkonosze Mountains and its well-preserved old town architecture.
  • D. Rzeszów
    Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
  • E. Świdnica
    Świdnica is a historic town in southwestern Poland known for its well-preserved medieval architecture and the UNESCO-listed Church of Peace.
  • 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_69ad85850c1481908a9e9c6242238de2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada617824c8190a293230041b2f1ea completed March 8, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235c3554c8190a94040955391a020 completed March 12, 2026, 3:40 a.m.
Created at: March 8, 2026, 3:05 p.m.