Triple
T28818184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epstein–Barr virus infection |
E727688
|
entity |
| Predicate | hasVirusGenus |
P2898
|
FINISHED |
| Object | Lymphocryptovirus |
—
|
NE NERFINISHED |
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: Lymphocryptovirus | Statement: [Epstein–Barr virus infection, hasVirusGenus, Lymphocryptovirus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVirusGenus Context triple: [Epstein–Barr virus infection, hasVirusGenus, Lymphocryptovirus]
-
A.
associatedWithVirusSpecies
Indicates a relationship where one entity is linked or connected to a particular virus species, typically through relevance, involvement, or attribution.
-
B.
pathogenGenus
chosen
Indicates that one entity is a pathogen belonging to, or classified under, the specified genus.
-
C.
diseaseVectorGenus
Indicates that one entity is the biological genus of organisms that serve as vectors transmitting the disease associated with the other entity.
-
D.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
-
E.
virusInvolved
Indicates that a virus participates in, influences, or is causally involved in a specified process, event, or relationship.
- 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_69f0319d09088190bbf14cdf1987792a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 28, 2026, 6:33 a.m.