Triple
T18426543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XY model |
E450153
|
entity |
| Predicate | typicalLatticeDimension |
P77135
|
FINISHED |
| Object | two-dimensional |
—
|
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: two-dimensional | Statement: [XY model, typicalLatticeDimension, two-dimensional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLatticeDimension Context triple: [XY model, typicalLatticeDimension, two-dimensional]
-
A.
dimensionOfAssociatedLattice
chosen
Indicates the dimensionality (number of independent directions) of the lattice that is associated with a given object or structure.
-
B.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
C.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
D.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
E.
hasLatticeStructure
Indicates that one entity possesses or exhibits a lattice structure, meaning its elements are partially ordered such that any two elements have well-defined least upper and greatest lower bounds.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51b13ee88819091e7e007d17dcc73 |
completed | April 19, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 11:24 a.m.