Triple
T16120616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Naples |
E391124
|
entity |
| Predicate | traditionalReligionContext |
P9028
|
FINISHED |
| Object | Roman Catholicism |
—
|
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: Roman Catholicism | Statement: [Princess of Naples, traditionalReligionContext, Roman Catholicism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalReligionContext Context triple: [Princess of Naples, traditionalReligionContext, Roman Catholicism]
-
A.
typicalReligionContext
Indicates the usual or most common religious setting, tradition, or affiliation associated with an entity or situation.
-
B.
traditionalReligionName
Indicates that an entity has a name specifically associated with a traditional or indigenous religion.
-
C.
originReligionContext
Indicates the religious background or setting from which something or someone originates or is derived.
-
D.
traditionalReligionHighGod
Indicates that within a traditional religion, the entity functions as a supreme or highest deity (high god) in that belief system.
-
E.
religiousCulturalContext
chosen
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20200acac8190a47e6a917ff8dd34 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.