Triple

T21186910
Position Surface form Disambiguated ID Type / Status
Subject Archdiocese of Bologna E522104 entity
Predicate secondaryLanguageOfPastoralCare P9103 FINISHED
Object Italian 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: Italian | Statement: [Archdiocese of Bologna, secondaryLanguageOfPastoralCare, Italian]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryLanguageOfPastoralCare
Context triple: [Archdiocese of Bologna, secondaryLanguageOfPastoralCare, Italian]
  • A. secondaryLanguageContext
    Indicates that the associated information, interaction, or content occurs within or is tailored to a secondary (non-primary) language setting or usage context.
  • B. laterSecondaryLanguageOfAdministration
    Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
  • C. primaryLanguageSide2
    Indicates that the second entity in the relationship uses or is associated with the primary language specified.
  • D. suffixLanguage
    Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
  • E. hasSecondaryLanguage chosen
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • 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_69e0b50ef1d48190b063aa342667df22 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7302222788190aa55ee0ed7342498 completed April 21, 2026, 8:06 a.m.
PD Predicate disambiguation batch_69e5f6027c248190a170a36612bd337e completed April 20, 2026, 9:46 a.m.
Created at: April 16, 2026, 3:07 p.m.