Triple
T28440176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady Queen of Peace |
E715685
|
entity |
| Predicate | hasShrinesDedicated |
P174695
|
FINISHED |
| Object | various Marian shrines |
—
|
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: various Marian shrines | Statement: [Our Lady Queen of Peace, hasShrinesDedicated, various Marian shrines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShrinesDedicated Context triple: [Our Lady Queen of Peace, hasShrinesDedicated, various Marian shrines]
-
A.
hasShrinesIn
Indicates that one entity possesses or maintains shrines that are located within the area or domain of another entity.
-
B.
hasMajorShrine
Indicates that one entity serves as a principal or primary shrine dedicated to another entity.
-
C.
hasSummitShrines
Indicates that a location or geographic feature has shrines situated at or near its summit.
-
D.
numberOfShrines
Indicates the total count of shrines associated with a given entity or context.
-
E.
enshrines
Indicates that one entity formally preserves, protects, or honors another by giving it a permanent, often sacred or legally recognized, status.
- 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_69efd6b44550819094ae991b553d9fc3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6c5b7e46081909975b05f7298cc0e |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c49069e48190a3486b6254a6645b |
completed | May 3, 2026, 3:44 a.m. |
Created at: April 28, 2026, 1:45 a.m.