Triple

T4243701
Position Surface form Disambiguated ID Type / Status
Subject Secure Flight E95474 entity
Predicate privacySafeguard P15689 FINISHED
Object use of data only for watch list matching and security purposes 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: use of data only for watch list matching and security purposes | Statement: [Secure Flight, privacySafeguard, use of data only for watch list matching and security purposes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: privacySafeguard
Context triple: [Secure Flight, privacySafeguard, use of data only for watch list matching and security purposes]
  • A. privacyProperty
    Indicates that one entity has a characteristic, rule, or condition specifically related to privacy in the context of the relationship.
  • B. privacyCharacteristic chosen
    Indicates the specific privacy-related property or feature that characterizes how information is handled, protected, or exposed in a given context.
  • C. protects
    Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
  • D. safeguard
    Indicates taking protective actions to shield someone or something from harm, loss, or danger.
  • E. protectionMeasures
    Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
  • 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e8a676c8190ac2cb59e62613dd9 completed March 12, 2026, 11:38 p.m.
PD Predicate disambiguation batch_69b347f587148190a1830503459939b6 completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:05 p.m.