Triple
T30756259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wheels of If |
E783091
|
entity |
| Predicate | hasHistoricalSubgenre |
P127457
|
FINISHED |
| Object | alternate religious history |
—
|
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: alternate religious history | Statement: [The Wheels of If, hasHistoricalSubgenre, alternate religious history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalSubgenre Context triple: [The Wheels of If, hasHistoricalSubgenre, alternate religious history]
-
A.
hasHistoricalCategory
Indicates that something is associated with a particular historical classification, period, or type based on its past context or significance.
-
B.
hasNotableSubgenre
Indicates that one genre is recognized as a particularly significant or prominent subgenre of another genre.
-
C.
isAssociatedWithSubgenre
chosen
Indicates that one entity has a connection or linkage to a specific subgenre of a broader category.
-
D.
hasHistoricalSection
Indicates that something includes a dedicated part or segment that presents historical information or context.
-
E.
hasHistoricalSubstratum
Indicates that one entity is historically underlain or influenced by another, earlier cultural, linguistic, or structural layer.
- 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_69f224af8d8481908bea03890c5618be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: April 29, 2026, 8:39 p.m.