Triple

T13441788
Position Surface form Disambiguated ID Type / Status
Subject Sukiennice E320378 entity
Predicate hasNameInPolish P15778 FINISHED
Object Sukiennice E320378 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: Sukiennice | Statement: [Sukiennice, hasNameInPolish, Sukiennice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sukiennice
Context triple: [Sukiennice, hasNameInPolish, Sukiennice]
  • A. Sukiennice chosen
    Sukiennice is a historic Renaissance cloth hall and landmark market building located in the main square of Kraków, Poland.
  • B. Sokółka
    Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
  • C. Sokołówka
    Sokołówka is a small river in Poland known for flowing through the city of Łódź and its surrounding areas.
  • D. Szerzyny
    Szerzyny is a village in southern Poland located within the administrative region of Lesser Poland Voivodeship.
  • E. Sorkwity
    Sorkwity is a village in northern Poland known for its scenic lakeside setting and historic manor house, situated in the Warmian-Masurian Voivodeship.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee704ac8190b4c7f4e0d3a88494 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7399421908190a7750e37c89a73f6 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.