Triple
T2158279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Rota |
E47941
|
entity |
| Predicate | typeOfCaseSpecialization |
P31978
|
FINISHED |
| Object | marriage nullity |
—
|
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: marriage nullity | Statement: [Roman Rota, typeOfCaseSpecialization, marriage nullity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCaseSpecialization Context triple: [Roman Rota, typeOfCaseSpecialization, marriage nullity]
-
A.
typeOfCasesHandled
chosen
Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
-
B.
specialCaseOf
Indicates that one entity represents a more specific, exceptional, or restricted instance of the general situation, rule, or relationship expressed by another entity.
-
C.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
-
D.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
E.
typeOfAppeals
Indicates the specific category or kind of appeals associated with or applied to a given case, decision, or legal action.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe68fe0c8190beb5db003738a6e5 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.