Triple
T34421087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorez Alexandria |
E883530
|
entity |
| Predicate | religiousMusicBackground |
P134858
|
FINISHED |
| Object | church choir singing |
—
|
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: church choir singing | Statement: [Lorez Alexandria, religiousMusicBackground, church choir singing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousMusicBackground Context triple: [Lorez Alexandria, religiousMusicBackground, church choir singing]
-
A.
religiousGenre
Indicates that the subject is associated with or categorized under a religious genre, style, or tradition.
-
B.
devotionalMusic
chosen
Indicates a relationship where music is created, performed, or used as an expression of religious or spiritual devotion toward a deity, faith, or sacred context.
-
C.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
D.
religiousMood
Indicates a prevailing emotional or spiritual atmosphere associated with religious experience, practice, or devotion between entities.
-
E.
religiousTransmission
Indicates the passing on or spread of religious beliefs, practices, or traditions from one entity to another.
- 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_69f349c2e3b88190a67834eb5bcffeaf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
Created at: May 1, 2026, 2 a.m.