Triple
T16102830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac Vert (Passy) |
E390663
|
entity |
| Predicate | hasPhotogenicFeature |
P121927
|
FINISHED |
| Object | mirror-like reflections |
—
|
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: mirror-like reflections | Statement: [Lac Vert (Passy), hasPhotogenicFeature, mirror-like reflections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotogenicFeature Context triple: [Lac Vert (Passy), hasPhotogenicFeature, mirror-like reflections]
-
A.
hasPhotoFeature
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
B.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
-
C.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
D.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
E.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
- F. None of above. chosen
Provenance (4 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6976ec8190b499e99b196b0285 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 5 a.m.