Triple
T17366630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Momordica |
E422202
|
entity |
| Predicate | phytochemicalProperty |
P99391
|
FINISHED |
| Object | contains bitter triterpenoids |
—
|
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: contains bitter triterpenoids | Statement: [Momordica, phytochemicalProperty, contains bitter triterpenoids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: phytochemicalProperty Context triple: [Momordica, phytochemicalProperty, contains bitter triterpenoids]
-
A.
notablePhytochemistry
Indicates that an entity is characterized by significant or noteworthy chemical compounds or phytochemical properties.
-
B.
hasChemicalProperty
chosen
Indicates that an entity possesses or exhibits a specific chemical property or characteristic.
-
C.
secondaryMetabolite
Indicates that one entity is a secondary metabolite produced by, associated with, or derived from another entity (such as an organism, pathway, or gene).
-
D.
chemicalComponent
Indicates that one entity is a constituent chemical part or ingredient of another entity.
-
E.
hasChemicalClass
Indicates that an entity belongs to, or is categorized under, a particular chemical class based on its structural or compositional characteristics.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a50c9ec8190b518fdf80808af53 |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.