Triple
T29844693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Diocese of Ferns |
E757896
|
entity |
| Predicate | hasPastIssue |
P195311
|
FINISHED |
| Object | clerical sexual abuse cases |
—
|
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: clerical sexual abuse cases | Statement: [Roman Catholic Diocese of Ferns, hasPastIssue, clerical sexual abuse cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPastIssue Context triple: [Roman Catholic Diocese of Ferns, hasPastIssue, clerical sexual abuse cases]
-
A.
hasRecentIssue
Indicates that an entity is associated with an issue or problem that has occurred within a recent or specified time frame.
-
B.
hasBackIssues
Indicates that an entity experiences or possesses problems, conditions, or complications related to its back.
-
C.
wasIssueAt
Indicates that a particular issue existed or occurred at a specific time, place, or contextual point.
-
D.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
E.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
| PDg | Predicate description generation | batch_69fdbaa1313081908beea28a5597ae40 |
completed | May 8, 2026, 10:27 a.m. |
Created at: April 29, 2026, 5:41 p.m.