Triple
T21055855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digitalis purpurea |
E518707
|
entity |
| Predicate | hasImageFeature |
P142666
|
FINISHED |
| Object | spotted interior of corolla |
—
|
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: spotted interior of corolla | Statement: [Digitalis purpurea, hasImageFeature, spotted interior of corolla]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImageFeature Context triple: [Digitalis purpurea, hasImageFeature, spotted interior of corolla]
-
A.
hasPhotoFeature
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
B.
containsImage
Indicates that one entity includes or embeds an image as part of its content or structure.
-
C.
hasImageRole
Indicates that an image is associated with an entity in a specific functional or contextual role (e.g., thumbnail, icon, illustration).
-
D.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
-
E.
hasImageType
Indicates that an entity is associated with an image of a particular type or format.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7fc5c48190bdc4d75ab6a529a3 |
completed | April 21, 2026, 4:30 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:37 p.m.