Triple

T6115385
Position Surface form Disambiguated ID Type / Status
Subject Pińczów County E136347 entity
Predicate seat P75 FINISHED
Object Pińczów E210802 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: Pińczów | Statement: [Pińczów County, seat, Pińczów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pińczów
Context triple: [Pińczów County, seat, Pińczów]
  • A. Pińczów chosen
    Pińczów is a historic town in south-central Poland known for its Renaissance architecture and scenic location in the Nida River valley.
  • B. Czernichów
    Czernichów is a village in southern Poland that serves as the seat of its namesake rural administrative district within the Kraków metropolitan area.
  • C. Suchedniów
    Suchedniów is a small town in south-central Poland, known for its surrounding forests and lakes and its location within the Świętokrzyskie Voivodeship.
  • D. Puławy
    Puławy is a historic town in eastern Poland known for its classical palace-and-park complex and role as an important cultural and scientific center.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bc246e48190b4f3d52eb682aa45 completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cde6789ec081909b051b8ce1bde35d completed April 2, 2026, 3:46 a.m.
Created at: March 22, 2026, 4:14 p.m.