Triple

T1811154
Position Surface form Disambiguated ID Type / Status
Subject Nieuw-Vennep E40333 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Welgelegen
Welgelegen is a residential neighborhood within the town of Nieuw-Vennep in the Dutch province of North Holland.
 E204503 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: Welgelegen | Statement: [Nieuw-Vennep, hasNeighbourhood, Welgelegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Welgelegen
Context triple: [Nieuw-Vennep, hasNeighbourhood, Welgelegen]
  • A. Lichtstad
    Lichtstad is the Dutch nickname for the city of Eindhoven, reflecting its historic association with the lighting industry and companies like Philips.
  • B. Klaaswaal
    Klaaswaal is a village in the Dutch province of South Holland, known for its rural character and location on the island of Hoeksche Waard.
  • C. Graskop
    Graskop is a small tourist town in northeastern South Africa known as a gateway to the Panorama Route and nearby natural attractions like waterfalls and the Blyde River Canyon.
  • D. Wilrijk
    Wilrijk is a southern district of the Belgian city of Antwerp, known for its residential character and green spaces.
  • E. Graaff-Reinet
    Graaff-Reinet is a historic town in South Africa’s Eastern Cape, known as one of the country’s oldest settlements and a center of early Afrikaner history.
  • 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: Welgelegen
Triple: [Nieuw-Vennep, hasNeighbourhood, Welgelegen]
Generated description
Welgelegen is a residential neighborhood within the town of Nieuw-Vennep in the Dutch province of North Holland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Welgelegen
Target entity description: Welgelegen is a residential neighborhood within the town of Nieuw-Vennep in the Dutch province of North Holland.
  • A. Lichtstad
    Lichtstad is the Dutch nickname for the city of Eindhoven, reflecting its historic association with the lighting industry and companies like Philips.
  • B. Klaaswaal
    Klaaswaal is a village in the Dutch province of South Holland, known for its rural character and location on the island of Hoeksche Waard.
  • C. Graskop
    Graskop is a small tourist town in northeastern South Africa known as a gateway to the Panorama Route and nearby natural attractions like waterfalls and the Blyde River Canyon.
  • D. Wilrijk
    Wilrijk is a southern district of the Belgian city of Antwerp, known for its residential character and green spaces.
  • E. Graaff-Reinet
    Graaff-Reinet is a historic town in South Africa’s Eastern Cape, known as one of the country’s oldest settlements and a center of early Afrikaner history.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65c64bc08190b993216890752b46 completed March 6, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf5b1dbc8190a57430bf129173e4 completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc0a3fdd88190b0ffa98db1b5cf80 completed March 8, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69adc1304a808190a999e71dfa39162a completed March 8, 2026, 6:34 p.m.
Created at: March 4, 2026, 7:32 p.m.