Triple
T23523429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czorsztyn Castle |
E574567
|
entity |
| Predicate | facesAcross |
P25568
|
FINISHED |
| Object | Czorsztyn Lake to Niedzica Castle |
—
|
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: Czorsztyn Lake to Niedzica Castle | Statement: [Czorsztyn Castle, facesAcross, Czorsztyn Lake to Niedzica Castle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesAcross Context triple: [Czorsztyn Castle, facesAcross, Czorsztyn Lake to Niedzica Castle]
-
A.
numberOfFaces
Indicates the relationship that specifies how many faces a given object or entity has.
-
B.
facesArea
Indicates that one entity is oriented toward, overlooks, or has its primary exposure directed toward a specified area.
-
C.
facesAssociatedWith
Indicates that there is a connection or linkage between certain faces (e.g., facial instances or representations) and related entities, contexts, or records.
-
D.
hasTwoMainFaces
Indicates that an entity possesses exactly two primary or most prominent faces or sides.
-
E.
facesBuilding
chosen
Indicates that one building is oriented toward and directly faces another building.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1ac71ec8881909bfb706efdc2518f |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:09 p.m.