Triple
T15739950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Podophyllum |
E381574
|
entity |
| Predicate | medicalUseOfCompounds |
P40313
|
FINISHED |
| Object | anticancer drugs |
—
|
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: anticancer drugs | Statement: [Podophyllum, medicalUseOfCompounds, anticancer drugs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalUseOfCompounds Context triple: [Podophyllum, medicalUseOfCompounds, anticancer drugs]
-
A.
medicinalUse
chosen
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
B.
potentialTherapeuticUse
Indicates that something is being considered or investigated as a possible treatment or therapy for a condition or disease.
-
C.
usesChemistry
Indicates that one entity applies or relies on chemistry, chemical methods, or chemical principles in relation to another entity or context.
-
D.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
E.
commonCompound
Indicates that the two entities share at least one chemical compound in common.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.