Triple

T796753
Position Surface form Disambiguated ID Type / Status
Subject Dubai Airshow E17038 entity
Predicate safetyAndSecurityFocus P2368 FINISHED
Object airport security 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: airport security | Statement: [Dubai Airshow, safetyAndSecurityFocus, airport security]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: safetyAndSecurityFocus
Context triple: [Dubai Airshow, safetyAndSecurityFocus, airport security]
  • A. safety
    Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
  • B. securityArrangementsBy
    Indicates that one entity is responsible for providing, organizing, or overseeing security arrangements for another entity or situation.
  • C. securityFeature chosen
    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.
  • D. aimsToProtect
    Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
  • E. security
    Indicates that an entity provides protection, safety measures, or safeguards to another entity or against specific threats or risks.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7b172e88190a26d31c9075b81fb completed March 1, 2026, 8:55 p.m.
PD Predicate disambiguation batch_69a4a5122a008190b0c621b7bc588d41 completed March 1, 2026, 8:44 p.m.
Created at: March 1, 2026, 7:38 p.m.