Triple
T19748794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian Hour of Grace |
E474320
|
entity |
| Predicate | hasCommonElement |
P137176
|
FINISHED |
| Object | recitation of the Rosary |
—
|
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: recitation of the Rosary | Statement: [Marian Hour of Grace, hasCommonElement, recitation of the Rosary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonElement Context triple: [Marian Hour of Grace, hasCommonElement, recitation of the Rosary]
-
A.
hasCommonValue
Indicates that two or more entities share at least one identical value or attribute in common.
-
B.
hasCommonReference
Indicates that two or more entities share the same source, citation, or referential basis.
-
C.
hasCommonRepresentative
Indicates that two or more entities share the same person or organization acting as their representative.
-
D.
hasCommonSpace
Indicates that two or more entities share access to the same physical or virtual area intended for joint or overlapping use.
-
E.
hasCommonShape
Indicates that two or more entities share the same or a very similar geometric or visual shape.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65296fa80819085aa4a18153531cf |
completed | April 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:47 p.m.