Triple
T15799471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cimicifuga |
E383060
|
entity |
| Predicate | hasChemicalConstituent |
P67837
|
FINISHED |
| Object | triterpene glycosides |
—
|
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: triterpene glycosides | Statement: [Cimicifuga, hasChemicalConstituent, triterpene glycosides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChemicalConstituent Context triple: [Cimicifuga, hasChemicalConstituent, triterpene glycosides]
-
A.
containsChemical
Indicates that one entity includes or has within it a specified chemical substance.
-
B.
chemicalComponent
chosen
Indicates that one entity is a constituent chemical part or ingredient of another entity.
-
C.
hasChemicalClass
Indicates that an entity belongs to, or is categorized under, a particular chemical class based on its structural or compositional characteristics.
-
D.
hasChemicalProperty
Indicates that an entity possesses or exhibits a specific chemical property or characteristic.
-
E.
chemicallyRelatedTo
Indicates a relationship where two entities are connected through a chemical association, such as sharing structural features, participating in related reactions, or being derivable from one another chemically.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e00d348190bc98917c4098ec2f |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.