Triple

T497170
Position Surface form Disambiguated ID Type / Status
Subject iPhone E10318 entity
Predicate hasFeature P182 FINISHED
Object Siri voice assistant E41436 NE 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: Siri voice assistant | Statement: [iPhone, hasFeature, Siri voice assistant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siri voice assistant
Context triple: [iPhone, hasFeature, Siri voice assistant]
  • A. Siri chosen
    Siri is Apple's intelligent voice-controlled virtual assistant that performs tasks, answers questions, and controls devices across the Apple ecosystem.
  • B. Google Assistant
    Google Assistant is Google's AI-powered virtual assistant that provides voice-activated help, information, and smart device control across phones, speakers, watches, and other connected devices.
  • C. Alexa
    Alexa is Amazon’s cloud-based virtual assistant that uses voice interaction to control smart devices, answer questions, and perform a variety of digital tasks.
  • D. Versoix
    Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
  • E. HomePod
    HomePod is Apple’s smart speaker that integrates Siri voice control with high-quality audio playback and seamless connectivity to the Apple ecosystem.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f116f1b4819082f88d6c747368ae completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a481ee2e348190b26b02990b4fb866 completed March 1, 2026, 6:14 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.