Triple

T16364641
Position Surface form Disambiguated ID Type / Status
Subject Brabantian dialects E397403 entity
Predicate hasVariety P455 FINISHED
Object Kempenlands
Kempenlands is a regional variety of the Brabantian dialect spoken in the Kempen area of the Low Countries.
E1208502 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: Kempenlands | Statement: [Brabantian dialects, hasVariety, Kempenlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kempenlands
Context triple: [Brabantian dialects, hasVariety, Kempenlands]
  • A. Kessingland
    Kessingland is a coastal village and civil parish in Suffolk, England, known for its long shingle beach and seaside tourism.
  • B. Hellingly
    Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
  • C. Heiligerlee
    Heiligerlee is a small village in the Dutch province of Groningen, known historically for the 1568 Battle of Heiligerlee, one of the first battles of the Eighty Years' War.
  • D. Stanground
    Stanground is a residential suburb and former village located within the city of Peterborough in Cambridgeshire, England.
  • E. Harlingerland
    Harlingerland is a historic coastal region in East Frisia in northwestern Germany, known for its North Sea landscape, dike systems, and traditional Frisian culture.
  • 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: Kempenlands
Triple: [Brabantian dialects, hasVariety, Kempenlands]
Generated description
Kempenlands is a regional variety of the Brabantian dialect spoken in the Kempen area of the Low Countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kempenlands
Target entity description: Kempenlands is a regional variety of the Brabantian dialect spoken in the Kempen area of the Low Countries.
  • A. Kessingland
    Kessingland is a coastal village and civil parish in Suffolk, England, known for its long shingle beach and seaside tourism.
  • B. Hellingly
    Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
  • C. Heiligerlee
    Heiligerlee is a small village in the Dutch province of Groningen, known historically for the 1568 Battle of Heiligerlee, one of the first battles of the Eighty Years' War.
  • D. Stanground
    Stanground is a residential suburb and former village located within the city of Peterborough in Cambridgeshire, England.
  • E. Harlingerland
    Harlingerland is a historic coastal region in East Frisia in northwestern Germany, known for its North Sea landscape, dike systems, and traditional Frisian culture.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff3bb5e481909669164a37d76b19 completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dc0b3d4819089e6fba536ec8a11 completed May 10, 2026, 7:03 a.m.
NEDg Description generation batch_6a002f35af8081908ea9c3d0a991c396 completed May 10, 2026, 7:09 a.m.
NED2 Entity disambiguation (via description) batch_6a002fa14ee4819080b02b368c0080b9 completed May 10, 2026, 7:11 a.m.
Created at: April 10, 2026, 5:08 a.m.