Triple

T2054706
Position Surface form Disambiguated ID Type / Status
Subject Norway Pavilion E45646 entity
Predicate hasRetailProduct P35622 FINISHED
Object Norwegian souvenirs 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: Norwegian souvenirs | Statement: [Norway Pavilion, hasRetailProduct, Norwegian souvenirs]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRetailProduct
Context triple: [Norway Pavilion, hasRetailProduct, Norwegian souvenirs]
  • A. hasRetailOption
    Indicates that one entity offers, includes, or is associated with a particular retail option (such as a sales channel, purchase method, or retail configuration) for another entity.
  • B. hasRetailCategory
    Indicates that an entity is associated with a specific retail category or type of retail business.
  • C. hasRetailFormat
    Indicates that one entity operates or is organized according to a particular retail format or store type.
  • D. hasRetailUnits
    Indicates that one entity possesses, operates, or is associated with one or more retail units (such as stores or outlets).
  • E. hasRetailPresenceIn
    Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
  • F. None of above. chosen

Provenance (4 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9a8518081909ba95a8ef9321f12 completed March 7, 2026, 5:37 a.m.
PD Predicate disambiguation batch_69abb7abba508190b872f345d3ba51bb completed March 7, 2026, 5:29 a.m.
PDg Predicate description generation batch_69abb94ec400819097596732aabed854 completed March 7, 2026, 5:36 a.m.
Created at: March 4, 2026, 7:40 p.m.