Triple
T22875087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon (Eastern Christian hymnography) |
E567300
|
entity |
| Predicate | metricalModel |
P46136
|
FINISHED |
| Object | biblical canticles |
—
|
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: biblical canticles | Statement: [Canon (Eastern Christian hymnography), metricalModel, biblical canticles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metricalModel Context triple: [Canon (Eastern Christian hymnography), metricalModel, biblical canticles]
-
A.
metricalFeature
chosen
Indicates a relationship where one entity specifies or characterizes a metrical property or pattern of another entity.
-
B.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
C.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
D.
emblematicModel
Indicates that one entity serves as a representative or symbolic example of another entity, capturing its defining characteristics or ideals.
-
E.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f57a1ec8190b8c6a0080d97a2a2 |
completed | April 29, 2026, 3:47 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:39 p.m.