Triple

T264764
Position Surface form Disambiguated ID Type / Status
Subject LinkedIn E5698 entity
Predicate securityIncident P3249 FINISHED
Object 2012 password leak 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: 2012 password leak | Statement: [LinkedIn, securityIncident, 2012 password leak]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: securityIncident
Context triple: [LinkedIn, securityIncident, 2012 password leak]
  • A. security
    Indicates that an entity provides protection, safety measures, or safeguards to another entity or against specific threats or risks.
  • B. majorSecurityIssue chosen
    Indicates that the subject faces or causes a significant security vulnerability or threat.
  • C. securityProgram
    Indicates that an entity is associated with, participates in, or is governed by a security program, such as a set of policies, controls, or initiatives related to safety or protection.
  • D. securityAspect
    Indicates a relationship where something pertains to, represents, or characterizes a particular aspect or dimension of security.
  • E. securityFeature
    Indicates that an entity provides, embodies, or is associated with a mechanism or property intended to enhance safety, protection, or defense against threats or vulnerabilities.
  • 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_69a2587daeb081909591b9d30f80a271 completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a25d8f9bbc8190a13841e4de093a66 completed Feb. 28, 2026, 3:14 a.m.
PD Predicate disambiguation batch_69a25b6e07748190834022a65ba6d803 completed Feb. 28, 2026, 3:05 a.m.
Created at: Feb. 28, 2026, 2:56 a.m.