Triple
T11159687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divini Redemptoris |
E264000
|
entity |
| Predicate | hasLatinTitleMeaning |
P50424
|
FINISHED |
| Object | Of the Divine Redeemer |
—
|
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: Of the Divine Redeemer | Statement: [Divini Redemptoris, hasLatinTitleMeaning, Of the Divine Redeemer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLatinTitleMeaning Context triple: [Divini Redemptoris, hasLatinTitleMeaning, Of the Divine Redeemer]
-
A.
hasLatinTitle
Indicates that an entity possesses a title or name expressed in Latin.
-
B.
hasLatinTitleOf
Indicates that one entity has, uses, or is associated with the Latin-language title corresponding to another entity.
-
C.
fullLatinTitleTranslation
chosen
Indicates that one entity is the full translated version of another entity’s Latin title.
-
D.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
-
E.
hasLatinizedName
Indicates that an entity is associated with a version of its name that has been converted into Latin form or spelling.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8817a90819087820d5241c58851 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.