Triple
T14008708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omicron variant |
E337019
|
entity |
| Predicate | impactOnMonoclonalAntibodies |
P112141
|
FINISHED |
| Object | reduced effectiveness for several therapies |
—
|
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: reduced effectiveness for several therapies | Statement: [Omicron variant, impactOnMonoclonalAntibodies, reduced effectiveness for several therapies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnMonoclonalAntibodies Context triple: [Omicron variant, impactOnMonoclonalAntibodies, reduced effectiveness for several therapies]
-
A.
associatedWithAntibody
Indicates a relationship where something is linked or connected to a specific antibody, such as being produced by it, targeted by it, or otherwise functionally related to it.
-
B.
basedOnAntibody
Indicates that something is derived from, developed using, or fundamentally dependent on a specific antibody.
-
C.
immunity
Indicates that an entity is protected against or not affected by a particular agent, condition, or influence.
-
D.
antibodyType
Indicates the specific class or subtype of an antibody involved in the described relationship or context.
-
E.
efficacyAgainstSevereCOVID19
Indicates the degree to which an intervention reduces the risk or severity of developing severe COVID-19 disease.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed44f90819099ad08c09c066b56 |
completed | April 14, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:19 p.m.