Triple

T15682856
Position Surface form Disambiguated ID Type / Status
Subject Leiden E377622 entity
Predicate hasPart P35 FINISHED
Object Merenwijk
Merenwijk is a residential district in the Dutch city of Leiden, known for its post-war urban planning and diverse population.
E1521059 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: Merenwijk | Statement: [Leiden, hasPart, Merenwijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merenwijk
Context triple: [Leiden, hasPart, Merenwijk]
  • A. Wijdemeren
    Wijdemeren is a municipality in the Dutch province of North Holland, known for its lakes, waterways, and scenic rural landscapes.
  • B. 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.
  • C. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • D. Steenwijk
    Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
  • E. Oosterwijtwerd
    Oosterwijtwerd is a small village in the province of Groningen in the northern Netherlands, known for its rural character and historic church.
  • 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: Merenwijk
Triple: [Leiden, hasPart, Merenwijk]
Generated description
Merenwijk is a residential district in the Dutch city of Leiden, known for its post-war urban planning and diverse population.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Merenwijk
Target entity description: Merenwijk is a residential district in the Dutch city of Leiden, known for its post-war urban planning and diverse population.
  • A. Wijdemeren
    Wijdemeren is a municipality in the Dutch province of North Holland, known for its lakes, waterways, and scenic rural landscapes.
  • B. 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.
  • C. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • D. Steenwijk
    Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
  • E. Oosterwijtwerd
    Oosterwijtwerd is a small village in the province of Groningen in the northern Netherlands, known for its rural character and historic church.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f31b5b881908e46ecd9fc6048ab completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a96dfbd5481908eaaa45696e5b09e completed May 18, 2026, 4:34 a.m.
NEDg Description generation batch_6a0a980276bc81908e9f6c6596880a8d completed May 18, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_6a0a986105bc819082556e8dec156ab6 completed May 18, 2026, 4:41 a.m.
Created at: April 10, 2026, 4:16 a.m.