Triple
T28263420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beck Hopelessness Scale |
E712639
|
entity |
| Predicate | timeToAdminister |
P165740
|
FINISHED |
| Object | approximately 5–10 minutes |
—
|
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: approximately 5–10 minutes | Statement: [Beck Hopelessness Scale, timeToAdminister, approximately 5–10 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToAdminister Context triple: [Beck Hopelessness Scale, timeToAdminister, approximately 5–10 minutes]
-
A.
dosingInterval
Indicates the time period that should elapse between consecutive doses of a medication or treatment.
-
B.
laterAdministeredAs
Indicates that something was given or applied at a subsequent time, following an earlier event or condition.
-
C.
typicalDosingFrequency
Indicates how often a treatment or medication is usually administered within a standard dosing regimen.
-
D.
usualMonthsAdministered
Indicates the months in which something, typically a treatment or intervention, is normally administered.
-
E.
doseRegimen
Indicates the specific schedule, frequency, and amount with which a dose of a substance or medication is to be administered.
- F. None of above. chosen
Provenance (4 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a6babcc81908052c9907a99c882 |
completed | May 2, 2026, 8:11 p.m. |
Created at: April 27, 2026, 11:13 p.m.