Triple

T1097449
Position Surface form Disambiguated ID Type / Status
Subject Social Security number E24300 entity
Predicate privacyConcern P15689 FINISHED
Object widespread overuse beyond original purpose 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: widespread overuse beyond original purpose | Statement: [Social Security number, privacyConcern, widespread overuse beyond original purpose]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: privacyConcern
Context triple: [Social Security number, privacyConcern, widespread overuse beyond original purpose]
  • 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. concern
    Indicates that one entity is about, relates to, or is of interest or importance to another entity.
  • D. concernsRight
    Indicates that something is about or relates specifically to a legal or moral right held by an entity.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9a1d3108190b2a304fef429848d completed March 1, 2026, 10:11 p.m.
PD Predicate disambiguation batch_69a4b745ef3481909a7ce4647c8567b3 completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.