Triple
T38280424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dioscorides |
E1022066
|
entity |
| Predicate | describedApproximateNumberOfDrugs |
P108228
|
FINISHED |
| Object | about 600 plants, animals, and minerals |
—
|
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: about 600 plants, animals, and minerals | Statement: [Dioscorides, describedApproximateNumberOfDrugs, about 600 plants, animals, and minerals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describedApproximateNumberOfDrugs Context triple: [Dioscorides, describedApproximateNumberOfDrugs, about 600 plants, animals, and minerals]
-
A.
numberOfDescribedDrugs
chosen
Indicates the quantity of drugs that are being described or specified in a given context.
-
B.
typicalDoseCount
Indicates the usual number of doses administered or taken in a standard course of use.
-
C.
evaluatedDrug
Indicates that a particular drug has been assessed or tested, typically in the context of a study, experiment, or evaluation process.
-
D.
discoveredAsDrugIn
Indicates that something was first identified, developed, or recognized for use as a drug within a specified context, such as a study, project, or time period.
-
E.
developedDrugFor
Indicates that one entity created or formulated a drug intended to treat or address a medical condition associated with another entity.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: May 3, 2026, 4:30 p.m.