Triple

T1347055
Position Surface form Disambiguated ID Type / Status
Subject Haarlem E28594 entity
Predicate locatedNear P294 FINISHED
Object Bloemendaal E82295 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: Bloemendaal | Statement: [Haarlem, locatedNear, Bloemendaal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bloemendaal
Context triple: [Haarlem, locatedNear, Bloemendaal]
  • A. Bloemendaal chosen
    Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
  • B. Roosendaal
    Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • C. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • D. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • E. Weesp
    Weesp is a historic town in the province of North Holland in the Netherlands, known for its canals, fortified structures, and traditional Dutch architecture.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c2406c488190b2c04d54d9c5e94c completed March 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5187dfe008190ac60e042527e55b3 completed March 26, 2026, 11:29 a.m.
Created at: March 1, 2026, 7:56 p.m.