Triple

T13800382
Position Surface form Disambiguated ID Type / Status
Subject Book Fair in Gothenburg E331622 entity
Predicate hasThematicGuestCountry P63990 FINISHED
Object various guest of honour countries 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: various guest of honour countries | Statement: [Book Fair in Gothenburg, hasThematicGuestCountry, various guest of honour countries]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasThematicGuestCountry
Context triple: [Book Fair in Gothenburg, hasThematicGuestCountry, various guest of honour countries]
  • A. hasGuestCountryProgram chosen
    Indicates that an entity hosts or is associated with a program specifically designed for or involving a guest country.
  • B. notableHostCountries
    Indicates that certain countries are recognized as prominent or significant locations for hosting a particular event, activity, or entity.
  • C. hasNotableGuest
    Indicates that an entity has a guest who is distinguished, prominent, or otherwise noteworthy in some significant way.
  • D. hostCountryPerformer
    Indicates that a country serves as the host location for a given performer’s activities or performance.
  • E. hasCountryParty
    Indicates a relationship where a country is associated with a specific political party operating or recognized within it.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
PD Predicate disambiguation batch_69dbc85fb600819098a2aab48169be96 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:11 p.m.