Triple
T23774815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neptune Fountain (Boboli Gardens) |
E587638
|
entity |
| Predicate | hasViewRole |
P161
|
FINISHED |
| Object | focal point in garden axis |
—
|
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: focal point in garden axis | Statement: [Neptune Fountain (Boboli Gardens), hasViewRole, focal point in garden axis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewRole Context triple: [Neptune Fountain (Boboli Gardens), hasViewRole, focal point in garden axis]
-
A.
hasRole
chosen
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
B.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
C.
hasSafetyRole
Indicates that an entity holds a responsibility or function related to safety within a given context or system.
-
D.
hasLegalRole
Indicates that an entity holds a specific legal capacity, status, or function in relation to another entity or context.
-
E.
hasGlobalRole
Indicates that an entity holds a role or permission set that applies across an entire system or domain, rather than being limited to a specific scope or context.
- 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c46a19688190aa91f1f10ba5c4ee |
completed | April 29, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.