Triple
T7895167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Kournikova virus |
E183325
|
entity |
| Predicate | detectionByAntivirus |
P53467
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Anna Kournikova virus, detectionByAntivirus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detectionByAntivirus Context triple: [Anna Kournikova virus, detectionByAntivirus, true]
-
A.
detected
chosen
Indicates that an entity has observed, identified, or discovered the presence or occurrence of another entity or event.
-
B.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
C.
recognizedByIOC
Indicates that an entity (such as a sport, event, or organization) is officially acknowledged or sanctioned by the International Olympic Committee (IOC).
-
D.
notableMalware
Indicates that the entity is recognized as a significant or well-known piece of malware, often due to its impact, prevalence, or technical characteristics.
-
E.
detectorConcept
Indicates that one entity functions as a detector whose conceptual design, type, or detection principle is characterized or specified by the other entity.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a174574819084270dbb6fcbb7fe |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:01 p.m.