Triple

T3220127
Position Surface form Disambiguated ID Type / Status
Subject The Little Mermaid statue E67491 entity
Predicate touristRanking P16499 FINISHED
Object one of the most visited attractions in Copenhagen 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: one of the most visited attractions in Copenhagen | Statement: [The Little Mermaid statue, touristRanking, one of the most visited attractions in Copenhagen]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: touristRanking
Context triple: [The Little Mermaid statue, touristRanking, one of the most visited attractions in Copenhagen]
  • A. visitorAttractionRank chosen
    Indicates the relative ranking or position of a visitor attraction compared to other attractions, typically based on popularity, quality, or importance.
  • B. hasTourismRating
    Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
  • C. touristArrivalsRank
    Indicates the relative position of a place compared to others based on the number of tourists arriving there.
  • D. hasTouristRank
    Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
  • E. tourismDraw
    Indicates that one entity attracts tourists or visitor interest to another entity or location.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adab0ef2c88190ab89e3217438a2bf completed March 8, 2026, 4:59 p.m.
PD Predicate disambiguation batch_69ad9e0bb6c48190a0659c67d40ee37c completed March 8, 2026, 4:04 p.m.
Created at: March 8, 2026, 3:08 p.m.