Triple
T1103692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leqembi |
E25439
|
entity |
| Predicate | hasDrugClass |
P13744
|
FINISHED |
| Object | anti-amyloid beta monoclonal antibody |
—
|
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: anti-amyloid beta monoclonal antibody | Statement: [Leqembi, hasDrugClass, anti-amyloid beta monoclonal antibody]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrugClass Context triple: [Leqembi, hasDrugClass, anti-amyloid beta monoclonal antibody]
-
A.
hasNotableDrug
Indicates that an entity is associated with a drug that is considered notable or significant in some recognized context.
-
B.
typicalDosageCategories
Indicates the standard dosage ranges or categories typically associated with a given treatment, substance, or medication.
-
C.
typeOfRemedy
chosen
Indicates that one entity is a specific kind or category of remedy in relation to another entity.
-
D.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
E.
isSometimesClassifiedAs
Indicates that an entity is occasionally, but not consistently or universally, categorized under a particular type or class.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b7472c848190b0643872f67084a2 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:43 p.m.