Triple
T13308102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharpless asymmetric dihydroxylation |
E316987
|
entity |
| Predicate | stereocontrolType |
P6850
|
FINISHED |
| Object | ligand-controlled |
—
|
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: ligand-controlled | Statement: [Sharpless asymmetric dihydroxylation, stereocontrolType, ligand-controlled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stereocontrolType Context triple: [Sharpless asymmetric dihydroxylation, stereocontrolType, ligand-controlled]
-
A.
controlsType
Indicates that one entity has authority over, or the ability to direct or regulate, the type or category of another entity.
-
B.
typeOfControl
chosen
Indicates the specific manner or mechanism by which one entity exercises control or influence over another.
-
C.
supportsVolumeControl
Indicates that one entity provides the capability to adjust or manage the audio volume level of another entity.
-
D.
controlSurfaces
Indicates that one entity functions as a control surface or set of control surfaces used to influence, steer, or regulate the behavior or state of another entity.
-
E.
hasStereoOutput
Indicates that an entity provides or supports audio output in stereo (two-channel) format.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.