Triple

T7732329
Position Surface form Disambiguated ID Type / Status
Subject Bryan, Texas E175288 entity
Predicate hasSisterCity P919 FINISHED
Object Krosno, Poland E217525 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: Krosno, Poland | Statement: [Bryan, Texas, hasSisterCity, Krosno, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krosno, Poland
Context triple: [Bryan, Texas, hasSisterCity, Krosno, Poland]
  • A. 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.
  • B. Kock, Poland
    Kock, Poland is a small historic town in eastern Poland known for its role in several military engagements, including World War II battles.
  • C. Krosno chosen
    Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
  • D. Żarnowiec, Poland
    Żarnowiec, Poland is a small village in northern Poland known for its historic monastery and scenic rural surroundings.
  • E. Tychy, Poland
    Tychy, Poland is an industrial city in the Silesian region known for its major automotive manufacturing plants and brewing industry.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7033863d881909451a4f9675021a3 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b531a7f481908e4ff7f15b851070 completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:06 p.m.