Triple
T29186569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rasa (aesthetic flavor) |
E739882
|
entity |
| Predicate | goalInArt |
P12365
|
FINISHED |
| Object | to evoke a stable aesthetic mood |
—
|
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: to evoke a stable aesthetic mood | Statement: [Rasa (aesthetic flavor), goalInArt, to evoke a stable aesthetic mood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalInArt Context triple: [Rasa (aesthetic flavor), goalInArt, to evoke a stable aesthetic mood]
-
A.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or context.
-
B.
artisticIntention
chosen
Indicates that an action or creation is guided by a deliberate artistic purpose, concept, or expressive goal of its creator.
-
C.
artisticAmbition
Indicates a desire or drive to create, achieve, or excel in artistic or creative pursuits.
-
D.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
-
E.
goalInPractice
Indicates that a particular goal is pursued, applied, or worked toward within the context of a practice or training activity.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f66387e29881909faf9e3fe961f60a |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, noon