Triple
T9842799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anaphora of Saint Mark |
E239266
|
entity |
| Predicate | devotionalLanguageType |
P90292
|
FINISHED |
| Object | formal liturgical language |
—
|
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: formal liturgical language | Statement: [Anaphora of Saint Mark, devotionalLanguageType, formal liturgical language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: devotionalLanguageType Context triple: [Anaphora of Saint Mark, devotionalLanguageType, formal liturgical language]
-
A.
languageOfWorship
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
B.
devotionalTitle
Indicates that one entity serves as the devotional or religiously themed title associated with another entity.
-
C.
religiousTextLanguageOf
Indicates that a particular language is the language in which a given religious text is written or primarily expressed.
-
D.
devotionalObject
Indicates that one entity is used by or associated with another as an object of religious or spiritual devotion.
-
E.
languageOfChant
Indicates the language in which a chant is performed or expressed.
- F. None of above. chosen
Provenance (4 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb35c8e348190aa090c71bf6f30eb |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06ace53081909b5f81f382f6591e |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:33 p.m.