Triple

T21295822
Position Surface form Disambiguated ID Type / Status
Subject Zaan region E524918 entity
Predicate hasPart P35 FINISHED
Object Krommenie NE NERFINISHED

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: Krommenie | Statement: [Zaan region, hasPart, Krommenie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krommenie
Context triple: [Zaan region, hasPart, Krommenie]
  • A. Krommenie chosen
    Krommenie is a town in the Dutch province of North Holland, known as a former industrial village that is now part of the municipality of Zaanstad.
  • B. Krasnobród
    Krasnobród is a small town in southeastern Poland known for its historical role in World War II and as a local tourist and spa destination in the Roztocze region.
  • C. Murów
    Murów is a village in southwestern Poland that serves as the seat of the rural administrative district (gmina) of Murów in Opole Voivodeship.
  • D. Kromołów
    Kromołów is a historic district of the city of Zawiercie in southern Poland, known as the place where the Warta River begins.
  • E. Niedzica
    Niedzica is a village in southern Poland known for its historic castle overlooking the Czorsztyn Lake in the Pieniny Mountains.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385858ec8190bdc9c5cdcb8d4507 completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:04 p.m.