Triple
T31535748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mucuna pruriens |
E804595
|
entity |
| Predicate | L-DOPAContent |
P77758
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Mucuna pruriens, L-DOPAContent, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: L-DOPAContent Context triple: [Mucuna pruriens, L-DOPAContent, high]
-
A.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
-
B.
neurotransmitter
Indicates that one entity functions as a chemical messenger released by a neuron to transmit signals to another cell across a synapse.
-
C.
drugProduced
chosen
Indicates that a particular drug is manufactured or generated by a specified producer or source.
-
D.
isProdrugOf
Indicates that one substance is a precursor form that is metabolized in the body to produce the active form of another substance.
-
E.
canBeDopedWith
Indicates that one entity is capable of being modified or enhanced by introducing the other entity as a dopant.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8055f8081908f635fe04654b5fe |
completed | May 3, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:03 p.m.