Triple
T15733003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchwald–Hartwig amination |
E381391
|
entity |
| Predicate | baseExamples |
P120397
|
FINISHED |
| Object | sodium tert-butoxide |
—
|
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: sodium tert-butoxide | Statement: [Buchwald–Hartwig amination, baseExamples, sodium tert-butoxide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baseExamples Context triple: [Buchwald–Hartwig amination, baseExamples, sodium tert-butoxide]
-
A.
backendExample
Indicates that something serves as an example or illustrative instance within a backend or server-side context.
-
B.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
C.
standardExample
Indicates that something is a typical or canonical instance used to illustrate a general case or concept.
-
D.
toolUseExamples
Indicates that one entity provides example instances or demonstrations of how a particular tool is or can be used by another entity.
-
E.
modeExamples
Indicates that specific example instances are provided to illustrate or clarify a particular mode or manner in which something operates or occurs.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0b4d01c9c81909f6b611e8144c838 |
completed | April 16, 2026, 10:07 a.m. |
Created at: April 10, 2026, 4:46 a.m.