Triple
T28374722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | dihydroartemisinin |
E718725
|
entity |
| Predicate | discoveredAsDrugIn |
P173713
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [dihydroartemisinin, discoveredAsDrugIn, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discoveredAsDrugIn Context triple: [dihydroartemisinin, discoveredAsDrugIn, 1970s]
-
A.
developedDrugFor
Indicates that one entity created or formulated a drug intended to treat or address a medical condition associated with another entity.
-
B.
medicinalUse
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
C.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
-
D.
isFirstDrugApprovedFor
Indicates that a drug is the earliest or original medication approved for treating a particular condition, disease, or indication.
-
E.
partUsedMedicinally
Indicates that a specific part of an entity (such as a plant or organism) is used for medicinal purposes.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6b9a84ff88190ab5a71f7ef1e0dac |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b8fe147881908ba17483c7b13f05 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 28, 2026, 1:02 a.m.