Triple
T30040412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cap Sante |
E763283
|
entity |
| Predicate | hasViewpointArea |
P127904
|
FINISHED |
| Object | Cap Sante Park |
—
|
NE NERFINISHED |
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: Cap Sante Park | Statement: [Cap Sante, hasViewpointArea, Cap Sante Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewpointArea Context triple: [Cap Sante, hasViewpointArea, Cap Sante Park]
-
A.
hasViewingPointFor
chosen
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
B.
hasViewpointType
Indicates that something is associated with or characterized by a particular type or category of viewpoint or perspective.
-
C.
hasViewpointConcept
Indicates that something is associated with, characterized by, or defined through a particular viewpoint, perspective, or conceptual stance.
-
D.
hasViewpointStatus
Indicates that an entity holds a particular evaluative or perspectival status (e.g., stance, opinion, or viewpoint classification) with respect to something.
-
E.
hasObservationArea
Indicates that an entity possesses or includes a designated area from which observations or monitoring activities are conducted.
- 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_69f2246fb2b88190acff36bf7975c8f0 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 29, 2026, 6:52 p.m.