Triple

T10132181
Position Surface form Disambiguated ID Type / Status
Subject South Holland E226364 entity
Predicate containsCity P294 FINISHED
Object Ridderkerk E180392 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: Ridderkerk | Statement: [South Holland, containsCity, Ridderkerk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ridderkerk
Context triple: [South Holland, containsCity, Ridderkerk]
  • A. Ridderkerk chosen
    Ridderkerk is a town and municipality in the western Netherlands, situated near Rotterdam in the province of South Holland.
  • B. Grijpskerke
    Grijpskerke is a village in the Dutch province of Zeeland, located on the former island of Walcheren.
  • C. Valkenswaard
    Valkenswaard is a town in the southern Netherlands known for its strong equestrian culture and international show jumping events.
  • D. Rijkevoort
    Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
  • E. Nieuwerkerken
    Nieuwerkerken is a municipality in the Belgian province of Limburg, known for its rural character and small village communities.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd336cbf48190b647c69675d0b06f completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f0c0c588190870b2145be187908 completed April 10, 2026, 6:56 a.m.
Created at: March 30, 2026, 9:06 p.m.