Triple

T3933885
Position Surface form Disambiguated ID Type / Status
Subject Dommel E90861 entity
Predicate flowsThrough P225 FINISHED
Object Oisterwijk
Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
 E795717 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: Oisterwijk | Statement: [Dommel, flowsThrough, Oisterwijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oisterwijk
Context triple: [Dommel, flowsThrough, Oisterwijk]
  • A. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • B. Houten
    Houten is a Dutch town in the province of Utrecht, known for its bicycle-friendly urban design and as the home of the Royal Dutch Mint.
  • C. Weesp
    Weesp is a historic town in the province of North Holland in the Netherlands, known for its canals, fortified structures, and traditional Dutch architecture.
  • D. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • E. Zoetermeer
    Zoetermeer is a modern, rapidly grown satellite city of The Hague in the western Netherlands, known for its residential neighborhoods and light-rail connections.
  • 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: Oisterwijk
Triple: [Dommel, flowsThrough, Oisterwijk]
Generated description
Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oisterwijk
Target entity description: Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
  • A. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • B. Houten
    Houten is a Dutch town in the province of Utrecht, known for its bicycle-friendly urban design and as the home of the Royal Dutch Mint.
  • C. Weesp
    Weesp is a historic town in the province of North Holland in the Netherlands, known for its canals, fortified structures, and traditional Dutch architecture.
  • D. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • E. Zoetermeer
    Zoetermeer is a modern, rapidly grown satellite city of The Hague in the western Netherlands, known for its residential neighborhoods and light-rail connections.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedcab1808190bf653f29062cdddb completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69d100a1ad688190b1a2fc91ce3dbdc3 completed April 4, 2026, 12:14 p.m.
NEDg Description generation batch_69d10156670c8190b61ef6231c2e78d2 completed April 4, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_69d10235f46c8190ba8eeb9382649f62 completed April 4, 2026, 12:21 p.m.
Created at: March 9, 2026, 3:23 p.m.