Triple

T1678233
Position Surface form Disambiguated ID Type / Status
Subject The Vicar of Dibley E36280 entity
Predicate numberOfSpecials P16447 FINISHED
Object various Christmas and New Year specials 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 Christmas and New Year specials | Statement: [The Vicar of Dibley, numberOfSpecials, various Christmas and New Year specials]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfSpecials
Context triple: [The Vicar of Dibley, numberOfSpecials, various Christmas and New Year specials]
  • A. numberOfSpecialWards
    Indicates the count of wards that are designated as special within a given context or entity.
  • B. hasSpecialRules
    Indicates that certain entities are governed by additional or exceptional rules that differ from the standard ones.
  • C. includesSpecialEpisodes chosen
    Indicates that the subject collection or series contains one or more special, non-regular episodes.
  • D. specialEdition
    Indicates that an item is a distinct, limited, or enhanced version of a standard release, often with unique features, packaging, or content.
  • E. hasSpecialUnit
    Indicates that an entity possesses or is associated with a distinct, designated unit that has a special role, function, or status.
  • 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_69a886139ed081909af0940aa9313512 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aba644070c81908745b56d981fe273 completed March 7, 2026, 4:15 a.m.
PD Predicate disambiguation batch_69aa61b57a6881909373af287ef24799 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:29 p.m.