Triple
T12191254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divine Praises |
E290466
|
entity |
| Predicate | typicalLanguageOfRecitation |
P42338
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Divine Praises, typicalLanguageOfRecitation, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanguageOfRecitation Context triple: [Divine Praises, typicalLanguageOfRecitation, Latin]
-
A.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
B.
typicalLanguages
chosen
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
C.
languageOfPrimaryNarrations
Indicates the language in which the main or primary narrations are expressed or conveyed.
-
D.
languageOfCeremony
Indicates the language in which a ceremony is conducted or officially performed.
-
E.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:50 p.m.