Triple
T22398307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagerstroemia speciosa |
E553692
|
entity |
| Predicate | partUsedMedicinally |
P147501
|
FINISHED |
| Object | leaves |
—
|
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: leaves | Statement: [Lagerstroemia speciosa, partUsedMedicinally, leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partUsedMedicinally Context triple: [Lagerstroemia speciosa, partUsedMedicinally, leaves]
-
A.
medicinalUse
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
B.
isMedicinalPlant
Indicates that a plant is used for medicinal purposes, such as treating, preventing, or alleviating health conditions.
-
C.
traditionalUse
Indicates that something is used or practiced according to long-established customs, habits, or cultural traditions.
-
D.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
-
E.
hasPharmacopoeia
Indicates that a substance, preparation, or product is included in or governed by a specific pharmacopoeia or official drug standard.
- F. None of above. chosen
Provenance (4 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15861ac248190a967f534feea0265 |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e73597b51c8190aeff27f4779b82f3 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 8:46 p.m.