Triple

T14085568
Position Surface form Disambiguated ID Type / Status
Subject Strążyska Valley E338984 entity
Predicate nearestCity 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: [Strążyska Valley, nearestCity, Zakopane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zakopane
Context triple: [Strążyska Valley, nearestCity, 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. Szczyrk
    Szczyrk is a popular mountain resort town in southern Poland, known for its ski slopes, hiking trails, and scenic location in the Silesian Beskids.
  • E. Rzeszów
    Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5edff1b881909ea56dc2429ef2dd completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd27f8f388819096c7c33b90f9ac4c completed May 8, 2026, 12:02 a.m.
Created at: April 9, 2026, 10:21 p.m.