Triple
T36297023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel of Saint Catherine of Siena |
E893396
|
entity |
| Predicate | isContainedInBuildingType |
P75382
|
FINISHED |
| Object | basilica |
—
|
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: basilica | Statement: [Chapel of Saint Catherine of Siena, isContainedInBuildingType, basilica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isContainedInBuildingType Context triple: [Chapel of Saint Catherine of Siena, isContainedInBuildingType, basilica]
-
A.
containsBuildingType
Indicates that a location or area includes at least one building of the specified type.
-
B.
belongsToBuildingType
chosen
Indicates that something is classified as being of a particular building type.
-
C.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
D.
appliedToBuildingType
Indicates that something (such as a rule, measure, or classification) is specifically applicable to a particular type of building.
-
E.
occursInBuilding
Indicates that an event or activity takes place within a specific 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:09 p.m.