Triple

T11682850
Position Surface form Disambiguated ID Type / Status
Subject Podlaskie Voivodeship E277661 entity
Predicate containsTown P847 FINISHED
Object Siemiatycze E335521 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: Siemiatycze | Statement: [Podlaskie Voivodeship, containsTown, Siemiatycze]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemiatycze
Context triple: [Podlaskie Voivodeship, containsTown, Siemiatycze]
  • A. Siemiatycze chosen
    Siemiatycze is a small town in northeastern Poland known for its multicultural heritage and location near the Bug River.
  • B. Siemianowice Śląskie
    Siemianowice Śląskie is an industrial city in southern Poland, historically part of Upper Silesia and closely linked to the Katowice urban area.
  • C. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • D. Sianów
    Sianów is a small town in northwestern Poland known for its historical ties to the Pomerania region and its location near the Baltic coast.
  • E. Skrzyczne
    Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a462bb2881909238107d34c0a28d completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f76b9112948190a0dd747a67f8206a completed May 3, 2026, 3:36 p.m.
Created at: April 8, 2026, 9:40 p.m.