Triple
T20061733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABVD regimen |
E499490
|
entity |
| Predicate | drugClassIncluded |
P24605
|
FINISHED |
| Object | anthracycline |
—
|
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: anthracycline | Statement: [ABVD regimen, drugClassIncluded, anthracycline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drugClassIncluded Context triple: [ABVD regimen, drugClassIncluded, anthracycline]
-
A.
drugClass
chosen
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
B.
protectedDrugClassesInclude
Indicates that the specified set of protected drug classes includes the referenced drug class or classes.
-
C.
hasPharmacologicClass
Indicates that a drug or medicinal product belongs to a specific pharmacologic class based on its mechanism of action or therapeutic effect.
-
D.
evaluatedDrug
Indicates that a particular drug has been assessed or tested, typically in the context of a study, experiment, or evaluation process.
-
E.
drugGenericName
Indicates that a drug entity is associated with its generic (non-brand) name.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6637601dc8190a07fc20844093cb7 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.