Triple
T35184773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of the Roses |
E1015954
|
entity |
| Predicate | usesTitleForMary |
P21321
|
FINISHED |
| Object | Mary Help of Mothers |
—
|
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: Mary Help of Mothers | Statement: [Our Lady of the Roses, usesTitleForMary, Mary Help of Mothers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTitleForMary Context triple: [Our Lady of the Roses, usesTitleForMary, Mary Help of Mothers]
-
A.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
B.
usesTitleIn
Indicates that an entity is referred to using a particular title within a specified context or medium.
-
C.
reportedTitleOfMary
chosen
Indicates that the specified title is one that has been reported or recorded as belonging to Mary.
-
D.
usedTitleIn
Indicates that one entity employed or referenced another entity as a title in some context.
-
E.
usesTitleForHouses
Indicates that an entity applies or assigns a specific title or naming convention to houses.
- 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:02 p.m.