Triple
T4784953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | REGN-EB3 |
E106452
|
entity |
| Predicate | dosingRegimen |
P37218
|
FINISHED |
| Object | single-course intravenous administration |
—
|
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: single-course intravenous administration | Statement: [REGN-EB3, dosingRegimen, single-course intravenous administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dosingRegimen Context triple: [REGN-EB3, dosingRegimen, single-course intravenous administration]
-
A.
doseRegimen
Indicates the specific schedule, frequency, and amount with which a dose of a substance or medication is to be administered.
-
B.
hasDosingRegimen
chosen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
C.
dosingInterval
Indicates the time period that should elapse between consecutive doses of a medication or treatment.
-
D.
hasLoadingDoseRegimen
Indicates that an entity is associated with a specific initial (loading) dosing regimen administered to rapidly achieve a desired therapeutic level.
-
E.
hasMaintenanceDose
Indicates that an entity is associated with a specific ongoing dose used to maintain a desired therapeutic effect after initial treatment.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ae49ec81908f16248d22d1155f |
completed | March 20, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69bd622e1b408190806c15c61519fc74 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.