Triple
T38268974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary, Queen of Peace |
E1021149
|
entity |
| Predicate | hasDedications |
P201111
|
FINISHED |
| Object | churches |
—
|
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: churches | Statement: [Mary, Queen of Peace, hasDedications, churches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDedications Context triple: [Mary, Queen of Peace, hasDedications, churches]
-
A.
hasDedicationNote
Indicates that one entity includes or is associated with a specific dedication note directed toward another entity or purpose.
-
B.
hasDedicationAt
Indicates that something is formally dedicated, commemorated, or honored at a specific place or location.
-
C.
hasDedicationPurpose
Indicates that something is dedicated, devoted, or assigned to serve a particular purpose or function.
-
D.
dedicationBy
Indicates that one entity formally dedicates, commits, or devotes another entity (such as a work, resource, or effort) to a particular person, purpose, or cause.
-
E.
hasFictionalDedication
Indicates that one entity is dedicated or addressed to another entity within a fictional or imaginative context.
- 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_69f76dee198c8190bf5109421e47a658 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffc7b4c7f88190b6357a44e7f0940f |
completed | May 9, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69ffc755f09c8190995ca00d97336988 |
completed | May 9, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69ffc7b41e688190ad3b86d87c38888e |
completed | May 9, 2026, 11:48 p.m. |
Created at: May 3, 2026, 4:30 p.m.