Triple
T32367560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varna Orthodox community |
E827034
|
entity |
| Predicate | usesReligiousMusic |
P151835
|
FINISHED |
| Object | Byzantine chant |
—
|
NE NERFINISHED |
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: Byzantine chant | Statement: [Varna Orthodox community, usesReligiousMusic, Byzantine chant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesReligiousMusic Context triple: [Varna Orthodox community, usesReligiousMusic, Byzantine chant]
-
A.
religiousGenre
Indicates that the subject is associated with or categorized under a religious genre, style, or tradition.
-
B.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
C.
usesMusicFor
chosen
Indicates that one entity employs or applies music as a means, tool, or resource to achieve or support some purpose, activity, or effect for another entity or context.
-
D.
isNonReligious
Indicates that an entity does not adhere to, practice, or identify with any religion or religious belief system.
-
E.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: May 1, 2026, 12:50 a.m.