Triple
T4784950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | REGN-EB3 |
E106452
|
entity |
| Predicate | targetMolecule |
P37016
|
FINISHED |
| Object | Ebola virus glycoprotein GP |
—
|
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: Ebola virus glycoprotein GP | Statement: [REGN-EB3, targetMolecule, Ebola virus glycoprotein GP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetMolecule Context triple: [REGN-EB3, targetMolecule, Ebola virus glycoprotein GP]
-
A.
hasMolecularTarget
chosen
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).
-
B.
regulatoryTarget
Indicates that one entity is subject to control, influence, or governance by another entity under a regulatory or rule-based framework.
-
C.
targetsGene
Indicates that one entity is directed toward, acts upon, or is intended to affect a specific gene.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
hasDrugBankID
Indicates that an entity is associated with a specific identifier from the DrugBank database.
- 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.