Triple
T30124197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirror Stream |
E765642
|
entity |
| Predicate | photoOpportunityType |
P49165
|
FINISHED |
| Object | cityscape photography location |
—
|
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: cityscape photography location | Statement: [Mirror Stream, photoOpportunityType, cityscape photography location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photoOpportunityType Context triple: [Mirror Stream, photoOpportunityType, cityscape photography location]
-
A.
hasPhotoSpot
chosen
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
B.
missPhotogenicWinner
Indicates that an entity is the winner of a Miss Photogenic title or award in a given context.
-
C.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
-
D.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
E.
typeOfStills
Indicates that one entity is a specific kind or category of stills (e.g., a particular type or style within the broader class of still images or still photography).
- 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67dee13b08190a261b79b10a1f87c |
completed | May 2, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:13 p.m.