Triple
T18954587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhein II |
E463737
|
entity |
| Predicate | mostExpensivePhotographAtTime |
P133939
|
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: [Rhein II, mostExpensivePhotographAtTime, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostExpensivePhotographAtTime Context triple: [Rhein II, mostExpensivePhotographAtTime, true]
-
A.
wasOneOfMostExpensiveFilmsOf
Indicates that a film ranked among the most expensive films produced in the specified context (such as a given time period, region, or category).
-
B.
hasPhotographicSignificance
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
-
C.
bestTimeForPhotography
Indicates the most suitable or optimal time period for taking photographs, typically based on lighting or environmental conditions.
-
D.
hasPhotographicRecordSince
Indicates that a photographic record of an entity has existed continuously since a specified point in time.
-
E.
photographsTakenIn
Indicates that photographs were captured or taken within a specific location or place.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d546babc81909d4fc5b6b4441aac |
completed | April 20, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, noon