Triple

T4045504
Position Surface form Disambiguated ID Type / Status
Subject Heumen E84055 entity
Predicate borderedBy P224 FINISHED
Object Berg en Dal E84054 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: Berg en Dal | Statement: [Heumen, borderedBy, Berg en Dal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berg en Dal
Context triple: [Heumen, borderedBy, Berg en Dal]
  • A. Berg en Dal chosen
    Berg en Dal is a Dutch municipality in the province of Gelderland, known for its hilly landscape, forests, and proximity to the city of Nijmegen.
  • B. Kungsängen
    Kungsängen is a locality in Stockholm County, Sweden, serving as the administrative and population center of Upplands-Bro Municipality.
  • C. Løten
    Løten is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and historic connections to painter Edvard Munch.
  • D. Derendingen
    Derendingen is a municipality in the canton of Solothurn in northwestern Switzerland, known as a residential and industrial community near the city of Solothurn.
  • E. Vallentuna
    Vallentuna is a locality in Stockholm County, Sweden, known as a suburban community within the Stockholm metropolitan area.
  • 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb5f85d48190ba80a0a24fbe438a completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55652228c8190a9f301676deb0055 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.