Triple
T19673775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mkinvartsveri |
E472398
|
entity |
| Predicate | hasPhotogenicLandscape |
P121927
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mkinvartsveri, hasPhotogenicLandscape, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotogenicLandscape Context triple: [Mkinvartsveri, hasPhotogenicLandscape, true]
-
A.
hasPhotogenicFeature
chosen
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
D.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
E.
hasPhotographicSignificance
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416e19d881909248c4f778f7147a |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514eb37b8819091502cc954f70eba |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.