Triple

T11111583
Position Surface form Disambiguated ID Type / Status
Subject Plac Wilsona metro station E262768 entity
Predicate servesDistrict P82 FINISHED
Object Żoliborz E1114637 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: Żoliborz | Statement: [Plac Wilsona metro station, servesDistrict, Żoliborz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Żoliborz
Context triple: [Plac Wilsona metro station, servesDistrict, Żoliborz]
  • A. Żoliborz chosen
    Żoliborz is a residential district in northern Warsaw, Poland, known for its interwar modernist architecture, green spaces, and quiet, upscale character.
  • B. Zbrzyca
    Zbrzyca is a river in northern Poland that flows through the Pomeranian region before joining the Brda River.
  • C. Krosno
    Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
  • D. Brzesko
    Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
  • E. Myślibórz
    Myślibórz is a small historic town in northwestern Poland known for its medieval architecture and picturesque lakes.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79aa42ec4819085a2e802e00d9f02 completed April 9, 2026, 12:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0683b90819098864f73b6976517 completed May 8, 2026, 2:17 p.m.
Created at: April 8, 2026, 9:27 p.m.