Triple

T12063211
Position Surface form Disambiguated ID Type / Status
Subject A44 motorway E287225 entity
Predicate passesNear P416 FINISHED
Object Sassenheim 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: Sassenheim | Statement: [A44 motorway, passesNear, Sassenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sassenheim
Context triple: [A44 motorway, passesNear, Sassenheim]
  • A. Sassenheim chosen
    Sassenheim is a town in the Dutch province of South Holland, known historically for its bulb-growing industry and location within the Duin- en Bollenstreek (Dune and Bulb Region).
  • B. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • C. Assendelft
    Assendelft is a historic village in North Holland, Netherlands, known as one of the country’s oldest settlements and for its association with the painter Pieter Saenredam.
  • D. Stadshagen
    Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • E. Culemborg
    Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043f82248190b05692aa0dc178a8 completed April 10, 2026, 2:07 p.m.
Created at: April 8, 2026, 9:48 p.m.