Triple

T1899306
Position Surface form Disambiguated ID Type / Status
Subject Royal Dutch Mint E37655 entity
Predicate locatedIn P40 FINISHED
Object 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.
E660008 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: Houten | Statement: [Royal Dutch Mint, locatedIn, Houten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Houten
Context triple: [Royal Dutch Mint, locatedIn, Houten]
  • A. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • B. Hoofddorp
    Hoofddorp is the main town and administrative center of the municipality of Haarlemmermeer in the Netherlands.
  • 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. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • E. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • 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: Houten
Triple: [Royal Dutch Mint, locatedIn, Houten]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Houten
Target entity description: 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.
  • A. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • B. Hoofddorp
    Hoofddorp is the main town and administrative center of the municipality of Haarlemmermeer in the Netherlands.
  • 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. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • E. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb17181b0819090683c55fd1352cb completed March 7, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69c80294e8bc8190bfaab1d02e1640a6 completed March 28, 2026, 4:32 p.m.
NEDg Description generation batch_69c804638c1481909c72e58432a4eaff completed March 28, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_69c8050e70108190b2cc0d2d30ddf139 completed March 28, 2026, 4:42 p.m.
Created at: March 4, 2026, 7:35 p.m.