Triple

T10634398
Position Surface form Disambiguated ID Type / Status
Subject Vlissingen E250539 entity
Predicate hasSubdivision P747 FINISHED
Object Oost-Souburg
Oost-Souburg is a town in the Dutch province of Zeeland that forms part of the municipality of Vlissingen.
E876447 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: Oost-Souburg | Statement: [Vlissingen, hasSubdivision, Oost-Souburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oost-Souburg
Context triple: [Vlissingen, hasSubdivision, Oost-Souburg]
  • A. Zuidhorn
    Zuidhorn is a village and former municipality in the province of Groningen in the northern Netherlands, known for its rural character and proximity to the city of Groningen.
  • B. Numansdorp
    Numansdorp is a village in the western Netherlands known for its rural character and location on the island of Hoeksche Waard.
  • C. Rijsbergen
    Rijsbergen is a village in the Dutch province of North Brabant, located near the Belgian border and known for its rural character.
  • D. Groesbeek
    Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
  • E. Moosseedorf
    Moosseedorf is a municipality in the canton of Bern in Switzerland, known for its proximity to the city of Bern and the nearby Moossee lake.
  • 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: Oost-Souburg
Triple: [Vlissingen, hasSubdivision, Oost-Souburg]
Generated description
Oost-Souburg is a town in the Dutch province of Zeeland that forms part of the municipality of Vlissingen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oost-Souburg
Target entity description: Oost-Souburg is a town in the Dutch province of Zeeland that forms part of the municipality of Vlissingen.
  • A. Zuidhorn
    Zuidhorn is a village and former municipality in the province of Groningen in the northern Netherlands, known for its rural character and proximity to the city of Groningen.
  • B. Numansdorp
    Numansdorp is a village in the western Netherlands known for its rural character and location on the island of Hoeksche Waard.
  • C. Rijsbergen
    Rijsbergen is a village in the Dutch province of North Brabant, located near the Belgian border and known for its rural character.
  • D. Groesbeek
    Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
  • E. Moosseedorf
    Moosseedorf is a municipality in the canton of Bern in Switzerland, known for its proximity to the city of Bern and the nearby Moossee lake.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfab47bc819086684edc1b6dce74 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bbd64d8819089d55af875d39e45 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d9701de92881908c0b8f05eae97e35 completed April 10, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69d970f3f78081909bcb2dae6dae06d5 completed April 10, 2026, 9:51 p.m.
Created at: April 8, 2026, 9:03 p.m.