Triple
T30086683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | corticospinal tract |
E764619
|
entity |
| Predicate | percentageFibersCrossed |
P171577
|
FINISHED |
| Object | approximately 80–90 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 80–90 percent | Statement: [corticospinal tract, percentageFibersCrossed, approximately 80–90 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageFibersCrossed Context triple: [corticospinal tract, percentageFibersCrossed, approximately 80–90 percent]
-
A.
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.
-
B.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
C.
totalFiberStrands
Indicates the total number of fiber strands associated with or contained in a given entity or connection.
-
D.
lengthOfCrossing
Indicates the measured extent or distance spanned by a crossing from one side to the other.
-
E.
crossCount
Indicates the number of times one entity crosses or intersects another within a given context.
- 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_69f6a1ac56b88190a820434b65c9fa23 |
completed | May 3, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 29, 2026, 7:04 p.m.