Triple
T36600567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APHINITY |
E902901
|
entity |
| Predicate | therapeuticClassEvaluated |
P177980
|
FINISHED |
| Object | HER2-targeted monoclonal antibodies |
—
|
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: HER2-targeted monoclonal antibodies | Statement: [APHINITY, therapeuticClassEvaluated, HER2-targeted monoclonal antibodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: therapeuticClassEvaluated Context triple: [APHINITY, therapeuticClassEvaluated, HER2-targeted monoclonal antibodies]
-
A.
therapeuticClassStudied
chosen
Indicates that a particular therapeutic class is the focus or subject of a study or investigation.
-
B.
drugClassEvaluated
Indicates that the classification or category of a drug has been assessed or analyzed in a given context.
-
C.
therapeuticSubgroup
Indicates a relationship where one entity is classified as a therapeutic subgroup within the broader therapeutic categorization of another entity.
-
D.
evaluatedDrug
Indicates that a particular drug has been assessed or tested, typically in the context of a study, experiment, or evaluation process.
-
E.
evaluatesDrug
Indicates that an entity assesses or judges the properties, effectiveness, or impact of a drug.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:11 p.m.