Triple

T4823007
Position Surface form Disambiguated ID Type / Status
Subject Maeslantkering E107753 entity
Predicate nearbyCity P350 FINISHED
Object Hoek van Holland E89149 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: Hoek van Holland | Statement: [Maeslantkering, nearbyCity, Hoek van Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hoek van Holland
Context triple: [Maeslantkering, nearbyCity, Hoek van Holland]
  • A. Hoek van Holland chosen
    Hoek van Holland is a coastal town in the Netherlands known for its North Sea beaches and its strategic location at the mouth of the New Waterway shipping canal.
  • B. North Holland
    North Holland is a province in the western Netherlands known for encompassing the national capital, Amsterdam, as well as historic towns and North Sea coastline.
  • C. Zeeland
    Zeeland is a coastal province in the southwest of the Netherlands, known for its islands, peninsulas, and extensive dike and flood defense systems.
  • D. Hellevoetsluis
    Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
  • E. Kennemerland
    Kennemerland is a coastal historical region in the northwest of the Netherlands, known for its dunes, beaches, and old trading towns.
  • 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6caa95ec8190bea525dbf3a00477 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10b0ec0c8190bcd4503dd09667c7 completed March 21, 2026, 9:42 p.m.
Created at: March 20, 2026, 1:24 p.m.