Triple

T12280477
Position Surface form Disambiguated ID Type / Status
Subject Bistrița E292702 entity
Predicate twinTown P1072 FINISHED
Object Zielona Góra, Poland E149641 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: Zielona Góra, Poland | Statement: [Bistrița, twinTown, Zielona Góra, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zielona Góra, Poland
Context triple: [Bistrița, twinTown, Zielona Góra, Poland]
  • A. Gorzów Wielkopolski, Poland
    Gorzów Wielkopolski is a city in western Poland, known as one of the two capitals of the Lubusz Voivodeship and an important regional industrial and cultural center.
  • B. Zielona Góra chosen
    Zielona Góra is a city in western Poland known for its wine-making tradition and annual wine festival.
  • C. Lipno, Poland
    Lipno, Poland is a small town in north-central Poland’s Kuyavian-Pomeranian Voivodeship, known as the birthplace of prominent economist and reformer Leszek Balcerowicz.
  • D. Żarnowiec, Poland
    Żarnowiec, Poland is a small village in northern Poland known for its historic monastery and scenic rural surroundings.
  • E. 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.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf1ab8c8190a51f498bfda957d8 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6f46f08190839ba07ef6fac984 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.