Triple

T14683070
Position Surface form Disambiguated ID Type / Status
Subject MTU Maintenance E344835 entity
Predicate hasFacilityIn P12416 FINISHED
Object Rzeszów, Poland E220683 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: Rzeszów, Poland | Statement: [MTU Maintenance, hasFacilityIn, Rzeszów, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rzeszów, Poland
Context triple: [MTU Maintenance, hasFacilityIn, Rzeszów, Poland]
  • A. Rzeszów chosen
    Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
  • B. Złoczów, Poland
    Złoczów, Poland is a town in present-day Ukraine (historically part of Poland) known as the birthplace of Nobel Prize–winning chemist Roald Hoffmann.
  • C. Kozienice, Poland
    Kozienice is a historic town in east-central Poland known for its location along the Vistula River and proximity to the Kozienice Landscape Park.
  • D. Żarnowiec, Poland
    Żarnowiec, Poland is a small village in northern Poland known for its historic monastery and scenic rural surroundings.
  • E. Ustronie, Poland
    Ustronie is a locality in Poland known historically as the place where the renowned Polish violinist and composer Karol Lipiński died.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb56a51ec8190941684fd562a7182 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde18592088190892ae1cc371165be completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.