Triple
T34944502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Els Encantats |
E1007817
|
entity |
| Predicate | hasPhotoViewpoint |
P127904
|
FINISHED |
| Object | Estany de Sant Maurici |
—
|
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: Estany de Sant Maurici | Statement: [Els Encantats, hasPhotoViewpoint, Estany de Sant Maurici]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotoViewpoint Context triple: [Els Encantats, hasPhotoViewpoint, Estany de Sant Maurici]
-
A.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
B.
hasViewingPointFor
chosen
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
C.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
D.
hasPhotoFeature
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
E.
hasPanoramicView
Indicates that something offers a wide, unobstructed view over a broad surrounding area.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4 p.m.