Triple
T15639954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SUNY Fredonia |
E376039
|
entity |
| Predicate | hasArtsFocus |
P3740
|
FINISHED |
| Object | music, theatre, and visual arts |
—
|
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: music, theatre, and visual arts | Statement: [SUNY Fredonia, hasArtsFocus, music, theatre, and visual arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtsFocus Context triple: [SUNY Fredonia, hasArtsFocus, music, theatre, and visual arts]
-
A.
hasArtisticFocus
chosen
Indicates that an entity’s primary artistic attention, theme, or specialization is directed toward a particular subject, style, or medium.
-
B.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
-
C.
hasArtAndDesignSchool
Indicates that an entity possesses, hosts, or includes an art and design school as part of its structure or offerings.
-
D.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
-
E.
hasArtisticSchool
Indicates that an entity is associated with, belongs to, or is characterized by a particular artistic school or style.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed06b388190bfebb77fe70e7df1 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.