Triple
T10164546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Pedro de la Nave |
E233972
|
entity |
| Predicate | floorElevation |
P55992
|
FINISHED |
| Object | slightly raised presbytery |
—
|
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: slightly raised presbytery | Statement: [San Pedro de la Nave, floorElevation, slightly raised presbytery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorElevation Context triple: [San Pedro de la Nave, floorElevation, slightly raised presbytery]
-
A.
floorHeight
chosen
Indicates the vertical elevation or level at which a particular floor is positioned within a structure.
-
B.
floorAbove
Indicates that one floor is located directly above another floor in a vertical arrangement.
-
C.
floorAccess
Indicates that an entity is permitted to enter or use a specific floor or level within a building or structure.
-
D.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
E.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec6b96dc8190ae37d0d28e4c393b |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:09 p.m.