Triple
T12454063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerechtigkeitsbrunnen |
E297607
|
entity |
| Predicate | isOftenPhotographed |
P17748
|
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: [Gerechtigkeitsbrunnen, isOftenPhotographed, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenPhotographed Context triple: [Gerechtigkeitsbrunnen, isOftenPhotographed, true]
-
A.
oftenPhotographedAt
chosen
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
B.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
-
C.
photographsTakenIn
Indicates that photographs were captured or taken within a specific location or place.
-
D.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.