Triple
T17423165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pope Gregory XII |
E423667
|
entity |
| Predicate | helpedRestore |
P33868
|
FINISHED |
| Object | unity of the Catholic Church |
—
|
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: unity of the Catholic Church | Statement: [Pope Gregory XII, helpedRestore, unity of the Catholic Church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedRestore Context triple: [Pope Gregory XII, helpedRestore, unity of the Catholic Church]
-
A.
restored
Indicates that an entity has returned another entity to a previous or improved state, condition, or position after damage, loss, or alteration.
-
B.
restoredBy
Indicates that an entity has been returned to a previous or improved state through the actions or intervention of another entity.
-
C.
laterRestored
Indicates that something previously altered, damaged, or removed was subsequently brought back to its earlier state or condition.
-
D.
restoredInPart
Indicates that something has been brought back to a previous or improved state, but only partially rather than fully.
-
E.
helpedCause
chosen
Indicates that one entity contributed to bringing about, enabling, or facilitating an outcome or event involving another entity.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44238b418819095c6a013d3ff3b17 |
completed | April 19, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.