Triple

T13914045
Position Surface form Disambiguated ID Type / Status
Subject Jaskinia Mroźna E334569 entity
Predicate nearbySettlement 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: [Jaskinia Mroźna, nearbySettlement, Zakopane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zakopane
Context triple: [Jaskinia Mroźna, nearbySettlement, 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de27245c648190b2946845ce0fdbf8 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcdef1e4608190a137f340e06d5ddb completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:16 p.m.