Triple
T34763383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel of St. Ludmila |
E1002130
|
entity |
| Predicate | namedForRoleOfSaint |
P192246
|
FINISHED |
| Object | grandmother of Saint Wenceslaus |
—
|
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: grandmother of Saint Wenceslaus | Statement: [Chapel of St. Ludmila, namedForRoleOfSaint, grandmother of Saint Wenceslaus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForRoleOfSaint Context triple: [Chapel of St. Ludmila, namedForRoleOfSaint, grandmother of Saint Wenceslaus]
-
A.
saintName
Indicates that an entity has the specified name under which they are recognized or venerated as a saint.
-
B.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
C.
associatedSaintOccupation
Indicates the occupation or role that is linked to or held by a particular saint.
-
D.
portraysAsSaint
Indicates that one entity depicts or represents another entity as a saintly, holy, or morally exemplary figure.
-
E.
linkedToSaint
Indicates that one entity has a direct association or connection with a saint.
- 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_69f76db20dac8190b1e8d0ca4dc1d59f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69fd026757a081909911a59a78652709 |
completed | May 7, 2026, 9:21 p.m. |
Created at: May 3, 2026, 3:59 p.m.