Triple
T17708479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Mary’s Hospital buildings, West Palm Beach |
E441495
|
entity |
| Predicate | hasReligiousAffiliationInName |
P128667
|
FINISHED |
| Object | Catholic tradition |
—
|
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: Catholic tradition | Statement: [St. Mary’s Hospital buildings, West Palm Beach, hasReligiousAffiliationInName, Catholic tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousAffiliationInName Context triple: [St. Mary’s Hospital buildings, West Palm Beach, hasReligiousAffiliationInName, Catholic tradition]
-
A.
religiousName
Indicates that an entity has or is known by a name specifically associated with a religious role, identity, or context.
-
B.
hasEponymReligion
Indicates that a religion is named after or derived from the name of a particular person.
-
C.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
D.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
E.
religionName
Indicates the religious affiliation or belief system associated with an entity.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47299cd7881908aac13b84acb61f7 |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d018227c8190b6624a2199e765e8 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 10, 2026, 10:05 a.m.