Triple

T14020115
Position Surface form Disambiguated ID Type / Status
Subject Muiderpoortstation E337307 entity
Predicate connectsTo P845 FINISHED
Object Weesp station E489680 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: Weesp station | Statement: [Muiderpoortstation, connectsTo, Weesp station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weesp station
Context triple: [Muiderpoortstation, connectsTo, Weesp station]
  • A. Hilversum station
    Hilversum station is a major railway station in the Dutch city of Hilversum, serving as an important regional and commuter hub in the central Netherlands.
  • B. Weesp railway station chosen
    Weesp railway station is a Dutch railway station in the town of Weesp that serves as a regional hub connecting multiple lines within the Netherlands’ rail network.
  • C. ’s‑Hertogenbosch station
    ’s‑Hertogenbosch station is a major railway hub in the southern Netherlands, serving as an important interchange for national and regional train services.
  • D. Barendrecht railway station
    Barendrecht railway station is a regional train station in the town of Barendrecht in the Netherlands, serving as a stop on the railway line south of Rotterdam.
  • E. Beekkant station
    Beekkant station is a Brussels Metro interchange station in the municipality of Molenbeek-Saint-Jean, serving multiple metro lines on the western side of the city.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f3c7cd88190b236382058581740 completed April 14, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd27fb2e6c81909e358862e012c49b completed May 8, 2026, 12:02 a.m.
Created at: April 9, 2026, 10:19 p.m.