Triple

T12063209
Position Surface form Disambiguated ID Type / Status
Subject A44 motorway E287225 entity
Predicate passesNear P416 FINISHED
Object Wassenaar E174773 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: Wassenaar | Statement: [A44 motorway, passesNear, Wassenaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wassenaar
Context triple: [A44 motorway, passesNear, Wassenaar]
  • A. Wassenaar chosen
    Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
  • B. Yerseke
    Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
  • C. Vandamm
    Vandamm is a surname, often a variant spelling of "van Damm," associated with various individuals in arts, entertainment, and other fields.
  • D. Esens
    Esens is a small historic town in Lower Saxony, Germany, known for its coastal North Sea location and traditional East Frisian character.
  • E. Wateringen
    Wateringen is a town in the western Netherlands that forms part of the municipality of Westland in the province of South Holland.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043f82248190b05692aa0dc178a8 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63ee0597c81909ad679a1ddece887 completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:48 p.m.