Triple

T11066976
Position Surface form Disambiguated ID Type / Status
Subject Commune of Drancy E261649 entity
Predicate hasTwinTown P919 FINISHED
Object Oswiecim E26048 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: Oswiecim | Statement: [Commune of Drancy, hasTwinTown, Oswiecim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oswiecim
Context triple: [Commune of Drancy, hasTwinTown, Oswiecim]
  • A. Oświęcim chosen
    Oświęcim is a town in southern Poland best known internationally as the location of the former Auschwitz concentration and extermination camp from World War II.
  • B. Chełmno
    Chełmno is a historic town in northern Poland, known for its well-preserved medieval Old Town and Gothic architecture.
  • C. Jedwabno
    Jedwabno is a small town in northern Poland located within the Warmian-Masurian Voivodeship, an area known for its lakes and forests.
  • D. Jaworzno
    Jaworzno is a city in southern Poland, located in the Silesian Voivodeship and known for its industrial heritage and role in the Upper Silesian urban area.
  • E. Kraśnik
    Kraśnik is a town in eastern Poland known for its historical architecture and location within the Lublin region.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79920428c81908db824ab54e08e8d completed April 9, 2026, 12:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8a4cdb8819080765d746f477089 completed April 18, 2026, 6:08 p.m.
Created at: April 8, 2026, 9:26 p.m.