Triple
T23278515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurycoma longifolia |
E588788
|
entity |
| Predicate | hasBioactiveCompounds |
P100523
|
FINISHED |
| Object | quassinoids |
—
|
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: quassinoids | Statement: [Eurycoma longifolia, hasBioactiveCompounds, quassinoids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBioactiveCompounds Context triple: [Eurycoma longifolia, hasBioactiveCompounds, quassinoids]
-
A.
hasBiologicalComponents
Indicates that an entity is composed of, contains, or is associated with one or more biological parts or substances.
-
B.
containsAlkaloids
Indicates that a substance, organism, or material has alkaloid compounds present within it.
-
C.
notablePhytochemistry
chosen
Indicates that an entity is characterized by significant or noteworthy chemical compounds or phytochemical properties.
-
D.
isMedicinalPlant
Indicates that a plant is used for medicinal purposes, such as treating, preventing, or alleviating health conditions.
-
E.
hasBioavailability
Indicates that a substance has a specified degree or measure of bioavailability, i.e., the proportion that enters circulation and can have an active effect.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957991108190ac82fa6dd355f722 |
completed | April 29, 2026, 5:22 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:49 p.m.