Triple

T10150978
Position Surface form Disambiguated ID Type / Status
Subject Biezelinge E232636 entity
Predicate adjacentSettlement P3883 FINISHED
Object Kapelle E72496 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: Kapelle | Statement: [Biezelinge, adjacentSettlement, Kapelle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapelle
Context triple: [Biezelinge, adjacentSettlement, Kapelle]
  • A. Kapelle chosen
    Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
  • B. Kappeln
    Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
  • C. Kaplice
    Kaplice is a small town in the Český Krumlov District of the South Bohemian Region of the Czech Republic, known for its historic center and proximity to the Bohemian Forest and the Austrian border.
  • D. Agnietenkapel
    Agnietenkapel is a historic former chapel in Amsterdam now used primarily for academic and cultural events, notably associated with the University of Amsterdam.
  • E. Tellskapelle
    Tellskapelle is a small lakeside chapel in Switzerland commemorating the legendary folk hero William Tell and his association with Lake Lucerne.
  • 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_69ca84885e48819088a31b127cf44904 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec0584a48190b65daa8370555c27 completed April 2, 2026, 4:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e640d1e0819094d30556ccb958b0 completed April 5, 2026, 10:46 p.m.
Created at: March 30, 2026, 9:08 p.m.