Triple

T10043547
Position Surface form Disambiguated ID Type / Status
Subject Frans Hals Museum E205353 entity
Predicate touristRank P20205 FINISHED
Object major tourist attraction in Haarlem LITERAL 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: major tourist attraction in Haarlem | Statement: [Frans Hals Museum, touristRank, major tourist attraction in Haarlem]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: touristRank
Context triple: [Frans Hals Museum, touristRank, major tourist attraction in Haarlem]
  • A. hasTouristRank
    Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
  • B. visitorAttractionRank
    Indicates the relative ranking or position of a visitor attraction compared to other attractions, typically based on popularity, quality, or importance.
  • C. touristArrivalsRank
    Indicates the relative position of a place compared to others based on the number of tourists arriving there.
  • D. hasTourismRating
    Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
  • E. hasTouristPopularity chosen
    Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
  • F. None of above.

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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf61b3e08190b69bcf67b6a95342 completed April 2, 2026, 2:07 a.m.
PD Predicate disambiguation batch_69cd4b8d2280819089de27e57babd1f3 completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 8:55 p.m.