Triple
T16728683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichinen sanzen |
E406528
|
entity |
| Predicate | numericalStructure |
P8195
|
FINISHED |
| Object | 3000 realms |
—
|
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: 3000 realms | Statement: [Ichinen sanzen, numericalStructure, 3000 realms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericalStructure Context triple: [Ichinen sanzen, numericalStructure, 3000 realms]
-
A.
hasNumberInStructure
Indicates that an entity’s structure includes or contains a specific numerical value or component.
-
B.
number
chosen
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
C.
numericalProperty
Indicates that an entity is associated with a specific numeric value or measurable quantity.
-
D.
numericPartRepresents
Indicates that a numeric component of something stands for or encodes a specific value, property, or aspect of that thing.
-
E.
numericDecomposition
Indicates that a number is broken down into a set of component numbers or factors whose combination (e.g., sum or product) reconstructs the original value.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38749baa48190892b2e2b978f6eb6 |
completed | April 18, 2026, 1:29 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.