Triple

T3677643
Position Surface form Disambiguated ID Type / Status
Subject Vijfhuizen E78033 entity
Predicate hasLandmark P105 FINISHED
Object Fort Vijfhuizen
Fort Vijfhuizen is a historic Dutch fort that forms part of the UNESCO-listed Defence Line of Amsterdam, now often used for cultural and recreational purposes.
 E381486 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: Fort Vijfhuizen | Statement: [Vijfhuizen, hasLandmark, Fort Vijfhuizen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fort Vijfhuizen
Context triple: [Vijfhuizen, hasLandmark, Fort Vijfhuizen]
  • A. Voorburg
    Voorburg is a historic town in the Netherlands, now part of the municipality of Leidschendam-Voorburg, known for its rich cultural heritage and proximity to The Hague.
  • B. Soestdijk
    Soestdijk is a village in the Netherlands known for its historic royal residence, Soestdijk Palace.
  • C. ’s-Heer Arendskerke
    ’s-Heer Arendskerke is a small village in the Dutch province of Zeeland, known for its rural character and historic church.
  • D. Diksmuide
    Diksmuide is a historic town in western Belgium known for its World War I battlefields and memorials, particularly the Yser Tower.
  • E. Haaksbergen
    Haaksbergen is a town in the eastern Netherlands, near the German border, known for its rural surroundings and cross-border ties with neighboring German communities.
  • 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: Fort Vijfhuizen
Triple: [Vijfhuizen, hasLandmark, Fort Vijfhuizen]
Generated description
Fort Vijfhuizen is a historic Dutch fort that forms part of the UNESCO-listed Defence Line of Amsterdam, now often used for cultural and recreational purposes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fort Vijfhuizen
Target entity description: Fort Vijfhuizen is a historic Dutch fort that forms part of the UNESCO-listed Defence Line of Amsterdam, now often used for cultural and recreational purposes.
  • A. Voorburg
    Voorburg is a historic town in the Netherlands, now part of the municipality of Leidschendam-Voorburg, known for its rich cultural heritage and proximity to The Hague.
  • B. Soestdijk
    Soestdijk is a village in the Netherlands known for its historic royal residence, Soestdijk Palace.
  • C. ’s-Heer Arendskerke
    ’s-Heer Arendskerke is a small village in the Dutch province of Zeeland, known for its rural character and historic church.
  • D. Diksmuide
    Diksmuide is a historic town in western Belgium known for its World War I battlefields and memorials, particularly the Yser Tower.
  • E. Haaksbergen
    Haaksbergen is a town in the eastern Netherlands, near the German border, known for its rural surroundings and cross-border ties with neighboring German communities.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4643cf08190b2d10ddf4aac7407 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cde8bc5081909cfaa4a391b8aca1 completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4cf5535748190b5dc3f23d1692e51 completed March 14, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_69b4cfc29a18819087935c16f6ecd9e4 completed March 14, 2026, 3:02 a.m.
Created at: March 8, 2026, 3:25 p.m.