Triple

T21914733
Position Surface form Disambiguated ID Type / Status
Subject Gmina Łoniów E541154 entity
Predicate subdivisionName P747 FINISHED
Object Świętokrzyskie NE NERFINISHED

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: Świętokrzyskie | Statement: [Gmina Łoniów, subdivisionName, Świętokrzyskie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Świętokrzyskie
Context triple: [Gmina Łoniów, subdivisionName, Świętokrzyskie]
  • A. Świętokrzyskie chosen
    Świętokrzyskie is a voivodeship (province) in south-central Poland, known for the historic Holy Cross (Święty Krzyż) Mountains from which it takes its name.
  • B. Ogrodzieniec
    Ogrodzieniec is a town in southern Poland best known for the ruins of its medieval castle in the Kraków-Częstochowa Upland.
  • C. Częstochowa
    Częstochowa is a city in southern Poland best known as a major Catholic pilgrimage center, home to the Jasna Góra Monastery and the revered Black Madonna icon.
  • D. Skrzyczne
    Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
  • E. Ostrowiec Świętokrzyski
    Ostrowiec Świętokrzyski is a city in south-central Poland known for its steel industry and proximity to the Świętokrzyskie (Holy Cross) Mountains.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47c4b9c8190a5586a75f5f36453 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f123366cb88190a42aa741e1245fd9 completed April 28, 2026, 9:14 p.m.
Created at: April 16, 2026, 7:42 p.m.