Triple
T19276688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosary mysteries |
E482075
|
entity |
| Predicate | originalNumberOfMysteries |
P22920
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Rosary mysteries, originalNumberOfMysteries, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNumberOfMysteries Context triple: [Rosary mysteries, originalNumberOfMysteries, 15]
-
A.
numberOfMysteries
chosen
Indicates the quantity or count of mysteries associated with a given entity.
-
B.
numberOfNewMysteries
Indicates the count of newly introduced or discovered mysteries associated with an entity or context.
-
C.
mysterySet
Indicates that an entity belongs to a collection or group whose nature, contents, or defining criteria are unknown or intentionally unspecified.
-
D.
hadGreaterMysteries
Indicates that one entity possessed or was associated with more profound, secret, or advanced mysteries than another entity.
-
E.
firstMystery
Indicates that something is the earliest or initial instance within a set whose nature or details are unknown or unspecified.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbd5f34819086535f28fd880411 |
completed | April 20, 2026, 10:11 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:29 p.m.