Triple
T30086798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betz cells |
E764621
|
entity |
| Predicate | hasCellBodyLocation |
P168426
|
FINISHED |
| Object | deep part of 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: deep part of layer V | Statement: [Betz cells, hasCellBodyLocation, deep part of layer V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCellBodyLocation Context triple: [Betz cells, hasCellBodyLocation, deep part of layer V]
-
A.
cellBodiesLocatedIn
chosen
Indicates that the cell bodies of a group of cells are situated within a specified anatomical region or structure.
-
B.
hasBodyDiscoveryLocation
Indicates the location where a body was found or discovered.
-
C.
hasLocationComponent
Indicates that something includes, is associated with, or is composed of a specific location-related part or element.
-
D.
hasCells
Indicates that an entity contains, is composed of, or is associated with one or more cells.
-
E.
hasLocalBody
Indicates that an entity is governed, administered, or represented by a specific local governing body or authority.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 29, 2026, 7:04 p.m.