Triple

T7895168
Position Surface form Disambiguated ID Type / Status
Subject Anna Kournikova virus E183325 entity
Predicate mitigationMethod P49797 FINISHED
Object up‑to‑date antivirus software 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: up‑to‑date antivirus software | Statement: [Anna Kournikova virus, mitigationMethod, up‑to‑date antivirus software]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mitigationMethod
Context triple: [Anna Kournikova virus, mitigationMethod, up‑to‑date antivirus software]
  • A. controlMeasure
    Indicates a relationship where one entity implements or applies a method, action, or mechanism to regulate, mitigate, or manage a risk, process, or condition associated with another entity.
  • B. protectionMeasures chosen
    Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
  • C. countermeasuresFaced
    Indicates that one entity has encountered or had to deal with countermeasures implemented by another entity.
  • D. hasEnvironmentalMitigation
    Indicates that an entity has associated measures, actions, or features intended to reduce, offset, or manage its negative environmental impacts.
  • E. providesProtectionAgainst
    Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
  • 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.