Triple

T22408337
Position Surface form Disambiguated ID Type / Status
Subject Lage Landen E553933 entity
Predicate hasDutchName P744 FINISHED
Object Lage Landen NE NERFINISHED

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: Lage Landen | Statement: [Lage Landen, hasDutchName, Lage Landen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lage Landen
Context triple: [Lage Landen, hasDutchName, Lage Landen]
  • A. Lage Landen chosen
    Lage Landen is the historical Low Countries region in Western Europe, roughly encompassing present-day Belgium, the Netherlands, and Luxembourg.
  • B. Rietlanden
    Rietlanden is a waterfront area in Amsterdam’s Eastern Docklands, known for its former industrial port functions and subsequent urban redevelopment.
  • C. Lansingerland
    Lansingerland is a Dutch municipality in the province of South Holland, known for its suburban communities and greenhouse horticulture near the city of Rotterdam.
  • D. Löwenberger Land
    Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
  • E. Länder
    Länder are the individual federal states that make up the Federal Republic of Germany, each with its own government and significant legislative powers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158badc008190a3f5afb520a25e5f completed April 29, 2026, 1:02 a.m.
Created at: April 16, 2026, 8:46 p.m.