Triple
T36297020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel of Saint Catherine of Siena |
E893396
|
entity |
| Predicate | hasSaintBuried |
P62966
|
FINISHED |
| Object | Saint Catherine of Siena |
—
|
NE NERFINISHED |
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: Saint Catherine of Siena | Statement: [Chapel of Saint Catherine of Siena, hasSaintBuried, Saint Catherine of Siena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSaintBuried Context triple: [Chapel of Saint Catherine of Siena, hasSaintBuried, Saint Catherine of Siena]
-
A.
isBuriedIn
Indicates that one entity is located beneath the ground or enclosed within another entity, typically as in a grave, tomb, or burial site.
-
B.
hasBurialsOf
chosen
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
-
C.
hasBuriedRemains
Indicates that one entity contains or is the location of the buried remains of another entity.
-
D.
isBuriedAliveBy
Indicates that one entity causes another entity to be placed in a grave or confined space and covered so as to be alive while buried.
-
E.
hasMassGraveOf
Indicates that a location or site contains a mass grave in which the referenced individuals or remains are buried.
- 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_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:09 p.m.