Triple
T27176478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sl(2,C) |
E683055
|
entity |
| Predicate | hasRootSpaceDecomposition |
P146159
|
FINISHED |
| Object | H ⊕ CE ⊕ CF |
—
|
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: H ⊕ CE ⊕ CF | Statement: [sl(2,C), hasRootSpaceDecomposition, H ⊕ CE ⊕ CF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRootSpaceDecomposition Context triple: [sl(2,C), hasRootSpaceDecomposition, H ⊕ CE ⊕ CF]
-
A.
hasDecomposition
Indicates that something can be broken down or separated into constituent parts, components, or simpler elements.
-
B.
hasBaseSpace
Indicates that one entity is defined or structured with respect to another entity that serves as its underlying base space.
-
C.
hasSolutionSpace
Indicates that there exists a set of possible solutions or outcomes associated with a given problem, constraint, or system.
-
D.
hasRootSystemSize
Indicates the relationship between an entity and the size or extent of its root system.
-
E.
hasCanonicalDecomposition
chosen
Indicates that an entity can be expressed as a standard or normalized combination of more basic components or parts.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 27, 2026, 9:26 a.m.