Triple

T2152566
Position Surface form Disambiguated ID Type / Status
Subject Face ID E47811 entity
Predicate falseMatchRate P7192 FINISHED
Object approximately 1 in 1,000,000 under Apple claims 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: approximately 1 in 1,000,000 under Apple claims | Statement: [Face ID, falseMatchRate, approximately 1 in 1,000,000 under Apple claims]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: falseMatchRate
Context triple: [Face ID, falseMatchRate, approximately 1 in 1,000,000 under Apple claims]
  • A. matchResult
    Indicates the outcome or final status produced by a particular match or game between participants.
  • B. successRate chosen
    Indicates the proportion or frequency with which attempts at a given action or process result in a successful outcome.
  • C. usesMatchesFrom
    Indicates that one entity relies on or incorporates matches (e.g., pattern matches, rule matches, or result matches) produced by another entity or process.
  • D. matchType
    Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
  • E. matches
    Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe48ad148190a7d6cc88fd38a660 completed March 7, 2026, 5:57 a.m.
PD Predicate disambiguation batch_69abbd9a60648190b20b116be5c7ad98 completed March 7, 2026, 5:54 a.m.
Created at: March 4, 2026, 7:44 p.m.