Triple

T11966145
Position Surface form Disambiguated ID Type / Status
Subject Baroque music E284793 entity
Predicate associatedAesthetic P102534 FINISHED
Object affect theory 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: affect theory | Statement: [Baroque music, associatedAesthetic, affect theory]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedAesthetic
Context triple: [Baroque music, associatedAesthetic, affect theory]
  • A. aestheticRole
    Indicates the role or function something has within an aesthetic or artistic context (e.g., as artwork, decoration, or design element).
  • B. associatedWithWorkOfArt
    Indicates a relationship in which an entity is connected or related to a specific work of art, such as through creation, contribution, ownership, or contextual association.
  • C. associatedWithArtForm
    Indicates a relationship where an entity is connected or linked to a particular art form, such as by practice, creation, representation, or influence.
  • D. relatedStyle
    Indicates that one style is associated with, similar to, or derived from another style in some relevant way.
  • E. artisticCharacteristic
    Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037adf5881908abe1a4e64a71f20 completed April 10, 2026, 2:04 p.m.
PD Predicate disambiguation batch_69d8bb40f30c8190a0e0719bd67542bf completed April 10, 2026, 8:56 a.m.
PDg Predicate description generation batch_69d8dd0ba0f88190b7d5e358c27ca184 completed April 10, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:46 p.m.