Triple

T3227263
Position Surface form Disambiguated ID Type / Status
Subject Giewont E67652 entity
Predicate locatedOnBorderOf P224 FINISHED
Object Zakopane municipality 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 municipality | Statement: [Giewont, locatedOnBorderOf, Zakopane municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zakopane municipality
Context triple: [Giewont, locatedOnBorderOf, Zakopane municipality]
  • 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. Polkowice
    Polkowice is a town in southwestern Poland known for its copper mining industry and location within the Lower Silesian region.
  • D. 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.
  • E. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service center.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb5e67c819082070d108d3613ba completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b33411537081908624477fca92296d completed March 12, 2026, 9:45 p.m.
Created at: March 8, 2026, 3:08 p.m.