Triple
T30087213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | optic tract |
E764630
|
entity |
| Predicate | containsCellType |
P121
|
FINISHED |
| Object | retinal ganglion cell axons |
—
|
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: retinal ganglion cell axons | Statement: [optic tract, containsCellType, retinal ganglion cell axons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCellType Context triple: [optic tract, containsCellType, retinal ganglion cell axons]
-
A.
cellTypeUsed
Indicates that a particular type of cell is employed or utilized in relation to another entity or process.
-
B.
hasSafetyCellType
Indicates that an entity is associated with a specific type of safety-related cell used for protection or risk mitigation.
-
C.
cellType
Indicates the classification relationship that specifies what type of cell an entity is or is associated with.
-
D.
affectsCellType
Indicates that one entity produces an effect or change on a specific type of cell.
-
E.
hasMemberType
chosen
Indicates that an entity includes or is associated with members belonging to a specified type or category.
- 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_69fed48d8e148190a99c0aea29f8a3ee |
completed | May 9, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fed3c82a24819095e614e31ac0307f |
completed | May 9, 2026, 6:27 a.m. |
Created at: April 29, 2026, 7:04 p.m.