Triple
T8902123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | primary motor cortex |
E211953
|
entity |
| Predicate | layerWithBetzCells |
P36580
|
FINISHED |
| Object | cortical layer V |
—
|
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: cortical layer V | Statement: [primary motor cortex, layerWithBetzCells, cortical layer V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: layerWithBetzCells Context triple: [primary motor cortex, layerWithBetzCells, cortical layer V]
-
A.
polygonCellsCause
Indicates that certain polygon-shaped cells bring about or are responsible for a particular effect or outcome in other entities or conditions.
-
B.
layerStructure
Indicates a relationship where one entity is organized in or assigned to a specific layer or hierarchical level within a structured system.
-
C.
layerOf
chosen
Indicates that one entity forms a distinct layer or stratum of another entity within a structured or composite whole.
-
D.
layerType
Indicates the specific kind or category of layer that an entity belongs to or is classified as.
-
E.
targetsLayer
Indicates that one entity is directed at, operates on, or is specifically intended to affect a particular layer within a layered structure or system.
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc642a104081908df2d64e8f9ad0c8 |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:55 p.m.