Triple
T30086684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | corticospinal tract |
E764619
|
entity |
| Predicate | percentageFibersUncrossed |
P172172
|
FINISHED |
| Object | approximately 10–20 percent |
—
|
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: approximately 10–20 percent | Statement: [corticospinal tract, percentageFibersUncrossed, approximately 10–20 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageFibersUncrossed Context triple: [corticospinal tract, percentageFibersUncrossed, approximately 10–20 percent]
-
A.
percentageFibersCrossed
Indicates the proportion of fibers that successfully cross from one side or region to another relative to the total number of fibers considered.
-
B.
totalFiberStrands
Indicates the total number of fiber strands associated with or contained in a given entity or connection.
-
C.
crossesUnder
Indicates that one entity passes beneath another entity’s path or structure, moving from one side to the other without intersecting it at the same elevation.
-
D.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
E.
notCrossing
Indicates that two entities do not intersect, overlap, or pass through each other in space or along their paths.
- F. None of above. chosen
Provenance (4 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_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a915ead881909463ae46419c343e |
completed | May 3, 2026, 1:47 a.m. |
Created at: April 29, 2026, 7:04 p.m.