Triple
T5448409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giudecca Canal |
E122306
|
entity |
| Predicate | hasScenicRole |
P27764
|
FINISHED |
| Object | popular for photography of Venice skyline |
—
|
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: popular for photography of Venice skyline | Statement: [Giudecca Canal, hasScenicRole, popular for photography of Venice skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicRole Context triple: [Giudecca Canal, hasScenicRole, popular for photography of Venice skyline]
-
A.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasNotableRoleIn
chosen
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
C.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
D.
hasStageRole
Indicates that an entity performs or holds a specific role or character in a staged performance or theatrical production.
-
E.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.