Triple
T1103713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leqembi |
E25439
|
entity |
| Predicate | hasDosingFrequency |
P7407
|
FINISHED |
| Object | every two weeks |
—
|
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: every two weeks | Statement: [Leqembi, hasDosingFrequency, every two weeks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDosingFrequency Context triple: [Leqembi, hasDosingFrequency, every two weeks]
-
A.
typicalDosageCategories
Indicates the standard dosage ranges or categories typically associated with a given treatment, substance, or medication.
-
B.
tienePeriodicidad
chosen
Indicates that something occurs, recurs, or is scheduled with a specific regular frequency or periodic pattern.
-
C.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
D.
commonRouteOfAdministration
Indicates that two or more substances share the same typical method or pathway by which they are administered to a subject.
-
E.
administeredWithin
Indicates that one entity is given, applied, or carried out inside the spatial or temporal bounds of another entity (such as a location, container, or time period).
- 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.