Triple

T13202546
Position Surface form Disambiguated ID Type / Status
Subject Ignudi E314275 entity
Predicate inArtLiterature P27711 FINISHED
Object frequently discussed in Michelangelo scholarship 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: frequently discussed in Michelangelo scholarship | Statement: [Ignudi, inArtLiterature, frequently discussed in Michelangelo scholarship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: inArtLiterature
Context triple: [Ignudi, inArtLiterature, frequently discussed in Michelangelo scholarship]
  • A. inLiterature chosen
    Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
  • B. literaryMuseOf
    Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
  • C. literarySubject
    Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
  • D. literaryCenter
    Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
  • E. literaryInterest
    Indicates that one entity has an interest in, appreciation of, or engagement with the literary works or writings of another entity.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf054f88190b05ced98d5a22a62 completed April 10, 2026, 11:51 p.m.
PD Predicate disambiguation batch_69d98bc6bc108190b5a6a265bf6e9fd4 completed April 10, 2026, 11:46 p.m.
Created at: April 9, 2026, 9:16 p.m.