Triple

T14442492
Position Surface form Disambiguated ID Type / Status
Subject Veerse Meer E358116 entity
Predicate nearbySettlement P350 FINISHED
Object Kamperland E356654 NE FINISHED

How this triple was built (2 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: Kamperland | Statement: [Veerse Meer, nearbySettlement, Kamperland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamperland
Context triple: [Veerse Meer, nearbySettlement, Kamperland]
  • A. Kamperland chosen
    Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
  • B. Arelerland
    Arelerland is a historical region in southeastern Belgium, centered around the town of Arlon and known for its Luxembourgish cultural and linguistic heritage.
  • C. Nemoland
    Nemoland is a popular open-air bar and live music venue located within Copenhagen’s autonomous neighborhood of Freetown Christiania.
  • D. Heidiland
    Heidiland is a popular Swiss tourist region in Eastern Switzerland, known for its alpine landscapes and associations with Johanna Spyri’s "Heidi" stories.
  • E. Backaland
    Backaland is a small settlement on the Orkney island of Eday in Scotland.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de915d28ec81909e72124e9dd67bfb completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bda6ee88190aeec77092eb3576a completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.