Triple
T8334790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frauenkirche (Dresden) |
E195160
|
entity |
| Predicate | usesOriginalStones |
P82152
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Frauenkirche (Dresden), usesOriginalStones, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesOriginalStones Context triple: [Frauenkirche (Dresden), usesOriginalStones, yes]
-
A.
originalStoneName
Indicates that an entity has or is associated with the original or primary name assigned to a particular stone.
-
B.
hasRegionalStone
Indicates that something possesses or is associated with a characteristic stone specific to a particular region.
-
C.
numberOfStones
Indicates the quantitative count of stones associated with a given entity or context.
-
D.
stoneUse
Indicates that one entity uses or employs stone as a material or tool for some purpose or activity.
-
E.
rebuiltInStone
Indicates that a previously existing structure was reconstructed using stone as the primary building material.
- 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd2ca648190991e398ba70caf8d |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:57 p.m.