Triple

T5734472
Position Surface form Disambiguated ID Type / Status
Subject Kazimierza Wielka E126465 entity
Predicate nearbyCity P350 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: [Kazimierza Wielka, nearbyCity, Pińczów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pińczów
Context triple: [Kazimierza Wielka, nearbyCity, 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. 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.
  • D. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service center.
  • E. Jasło
    Jasło is a small town in southeastern Poland, known as part of the historical region of Galicia and for its cultural and educational traditions.
  • 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02536706c8190a69665b75c8a38e9 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa512324819092e3a0b449cdb9ba completed March 28, 2026, 3:57 p.m.
Created at: March 22, 2026, 3:47 p.m.