Triple
T158494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosary |
E3228
|
entity |
| Predicate | languageOfPrayer |
P3115
|
FINISHED |
| Object | various vernacular languages |
—
|
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: various vernacular languages | Statement: [Rosary, languageOfPrayer, various vernacular languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPrayer Context triple: [Rosary, languageOfPrayer, various vernacular languages]
-
A.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
B.
languageOfCeremony
Indicates the language in which a ceremony is conducted or officially performed.
-
C.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
D.
religiousFunction
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
E.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2583169a0819081b658882e5bc452 |
completed | Feb. 28, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69a25660c2a48190b4174d5e6da3cb9d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.