Triple

T9910006
Position Surface form Disambiguated ID Type / Status
Subject Lommel E185115 entity
Predicate borderWith P224 FINISHED
Object Neerpelt E399686 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: Neerpelt | Statement: [Lommel, borderWith, Neerpelt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neerpelt
Context triple: [Lommel, borderWith, Neerpelt]
  • A. Neerpelt chosen
    Neerpelt is a town in the Belgian province of Limburg, known for its green surroundings and cultural events.
  • B. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • C. Zoersel
    Zoersel is a municipality in the Belgian province of Antwerp, known for its green residential character and wooded surroundings.
  • D. Schwansen
    Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
  • E. Nederasselt
    Nederasselt is a village in the Dutch province of Gelderland, located within the municipality of Heumen.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb51184d08190a0350f2722110811 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20db5979081909b8e292ac6bb7c2f completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.