Triple

T734651
Position Surface form Disambiguated ID Type / Status
Subject Overijssel E14902 entity
Predicate containsCity P294 FINISHED
Object Oldenzaal
Oldenzaal is a historic city in the eastern Netherlands known for its medieval center and location near the German border in the province of Overijssel.
E242770 NE FINISHED

How this triple was built (4 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: Oldenzaal | Statement: [Overijssel, containsCity, Oldenzaal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oldenzaal
Context triple: [Overijssel, containsCity, Oldenzaal]
  • A. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • B. Teylingen
    Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
  • C. Nissewaard
    Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
  • D. Zwijndrecht
    Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
  • E. Nieuwendijk
    Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oldenzaal
Triple: [Overijssel, containsCity, Oldenzaal]
Generated description
Oldenzaal is a historic city in the eastern Netherlands known for its medieval center and location near the German border in the province of Overijssel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oldenzaal
Target entity description: Oldenzaal is a historic city in the eastern Netherlands known for its medieval center and location near the German border in the province of Overijssel.
  • A. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • B. Teylingen
    Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
  • C. Nissewaard
    Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
  • D. Zwijndrecht
    Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
  • E. Nieuwendijk
    Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
  • F. None of above. chosen

Provenance (5 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5d8c6148190a468f2d95f7ec91f completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d7138f08190ae4055b31bd3cad1 completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5e6f8eb481908d75d2c648a88af4 completed March 9, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_69ae5edfe80481908c3304c917c9065b completed March 9, 2026, 5:47 a.m.
Created at: March 1, 2026, 7:37 p.m.