Triple

T7400139
Position Surface form Disambiguated ID Type / Status
Subject Silesian Beskids E170725 entity
Predicate hasPeak P8205 FINISHED
Object Skrzyczne E899472 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: Skrzyczne | Statement: [Silesian Beskids, hasPeak, Skrzyczne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skrzyczne
Context triple: [Silesian Beskids, hasPeak, Skrzyczne]
  • A. Skrzyczne chosen
    Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
  • B. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • C. Kruszwica
    Kruszwica is a historic town in central Poland, known for its medieval Mouse Tower, lakeside setting on Lake Gopło, and role as an early center of Polish statehood.
  • D. Ogrodzieniec
    Ogrodzieniec is a town in southern Poland best known for the ruins of its medieval castle in the Kraków-Częstochowa Upland.
  • E. Szczucin
    Szczucin is a small town in southern Poland, situated near the Vistula River and known historically as a local trade and transport hub.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f24dbf288190b8dfea455148841b completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a8c95ca081908ceaa89eef87fbc9 completed April 18, 2026, 3:52 p.m.
Created at: March 27, 2026, 3:10 p.m.