Triple
T4785000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mAb114 |
E106453
|
entity |
| Predicate | hasPharmacologicalEffect |
P58407
|
FINISHED |
| Object | reduction of Ebola virus replication |
—
|
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: reduction of Ebola virus replication | Statement: [mAb114, hasPharmacologicalEffect, reduction of Ebola virus replication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPharmacologicalEffect Context triple: [mAb114, hasPharmacologicalEffect, reduction of Ebola virus replication]
-
A.
hasPharmacologicClass
Indicates that a drug or medicinal product belongs to a specific pharmacologic class based on its mechanism of action or therapeutic effect.
-
B.
hasNotableDrug
Indicates that an entity is associated with a drug that is considered notable or significant in some recognized context.
-
C.
hasMolecularTarget
Indicates that one entity (such as a drug or compound) is directed toward, binds to, or specifically interacts with a particular molecular target (such as a protein, receptor, or gene).
-
D.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
E.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
- 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_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. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:22 p.m.