Triple
T1608427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Islanders |
E34559
|
entity |
| Predicate | primaryLogoMotif |
P23931
|
FINISHED |
| Object | stylized "NY" over Long Island silhouette |
—
|
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: stylized "NY" over Long Island silhouette | Statement: [New York Islanders, primaryLogoMotif, stylized "NY" over Long Island silhouette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLogoMotif Context triple: [New York Islanders, primaryLogoMotif, stylized "NY" over Long Island silhouette]
-
A.
primaryLogoTheme
chosen
Indicates the main stylistic or visual design theme associated with a logo.
-
B.
primaryEmblem
Indicates that one emblem is the main or most representative symbol associated with an entity.
-
C.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
D.
logoFeature
Indicates that an entity serves as a distinctive visual element or component within a logo.
-
E.
logoImage
Indicates the image that serves as the logo representing an 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fa6926081908bc78d15c0be3185 |
completed | March 5, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69a907c35f848190a2428c52e81d013e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.