Triple
T12679365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Common Admission Test |
E302904
|
entity |
| Predicate | administeredInMode |
P11436
|
FINISHED |
| Object | online |
—
|
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: online | Statement: [Common Admission Test, administeredInMode, online]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administeredInMode Context triple: [Common Admission Test, administeredInMode, online]
-
A.
administeredIn
Indicates that an action, treatment, or process is carried out or applied within a specific location, context, or jurisdiction.
-
B.
administeredWith
Indicates that two or more treatments, drugs, or interventions are given to a patient at the same time or as part of the same therapeutic regimen.
-
C.
typeOfAdministration
chosen
Indicates the specific form or system of administration applied to or governing an entity.
-
D.
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).
-
E.
administeredAs
Indicates that one entity is given or applied to another entity as a treatment, dose, or intervention.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b1dff48190923290555ece5d89 |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:21 p.m.