Triple
T10291983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | warfarin |
E241385
|
entity |
| Predicate | hasEnantiomer |
P88545
|
FINISHED |
| Object | S-warfarin |
—
|
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: S-warfarin | Statement: [warfarin, hasEnantiomer, S-warfarin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnantiomer Context triple: [warfarin, hasEnantiomer, S-warfarin]
-
A.
isEnantiomerOf
chosen
Indicates that two molecular entities are non-superimposable mirror images of each other, related by inversion of all chiral centers.
-
B.
isomer
Indicates that two chemical species share the same molecular formula but differ in the arrangement or orientation of their atoms, resulting in distinct structures or properties.
-
C.
hasChiralityComponents
Indicates that an entity’s chirality is determined by, or composed of, one or more specified chiral components.
-
D.
isChiralInStandardModel
Indicates that the entity’s behavior or interaction in the Standard Model depends on its handedness (left- or right-handed), i.e., it is not invariant under parity transformation.
-
E.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d35f048190a215493acdf1f718 |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.