Triple
T35679056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolianova |
E1030950
|
entity |
| Predicate | dedicatedSaintOfCathedral |
P22282
|
FINISHED |
| Object | Saint Pantaleon |
—
|
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 Pantaleon | Statement: [Dolianova, dedicatedSaintOfCathedral, Saint Pantaleon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dedicatedSaintOfCathedral Context triple: [Dolianova, dedicatedSaintOfCathedral, Saint Pantaleon]
-
A.
hasCathedralDedicatedTo
Indicates that one entity possesses or contains a cathedral whose dedication (to a saint, figure, or concept) is specifically associated with another entity.
-
B.
cathedralDedication
chosen
Indicates the religious figure, event, or concept to which a cathedral is formally dedicated.
-
C.
mainChurchPatron
Indicates that one entity serves as the primary patron or chief sponsoring supporter of a particular church.
-
D.
cathedralName
Indicates that an entity has the specified name of a cathedral.
-
E.
liturgicalDedication
Indicates that something (typically a religious building, object, or time) is formally dedicated or consecrated for use in a specific liturgical or worship context.
- 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.