Triple

T2243013
Position Surface form Disambiguated ID Type / Status
Subject Koksijde Air Base E49438 entity
Predicate location P40 FINISHED
Object Koksijde
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
 E246975 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: Koksijde | Statement: [Koksijde Air Base, location, Koksijde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Koksijde
Context triple: [Koksijde Air Base, location, Koksijde]
  • A. Wassenaar
    Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
  • B. Lonsee
    Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
  • C. Wilrijk
    Wilrijk is a southern district of the Belgian city of Antwerp, known for its residential character and green spaces.
  • D. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • E. Lesje
    Lesje is a central character in Margaret Atwood's novel "Life Before Man," portrayed as a paleontologist navigating complex personal relationships and questions of identity.
  • 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: Koksijde
Triple: [Koksijde Air Base, location, Koksijde]
Generated description
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Koksijde
Target entity description: Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
  • A. Wassenaar
    Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
  • B. Lonsee
    Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
  • C. Wilrijk
    Wilrijk is a southern district of the Belgian city of Antwerp, known for its residential character and green spaces.
  • D. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • E. Lesje
    Lesje is a central character in Margaret Atwood's novel "Life Before Man," portrayed as a paleontologist navigating complex personal relationships and questions of identity.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0c017548190a71fb4a0e2a8189f completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b10c38c8190af7d6d99f9377df1 completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6bbdef14819084b96389435ca080 completed March 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c2cfac48190b0425088e79cd122 completed March 9, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:47 p.m.