Triple

T1052192
Position Surface form Disambiguated ID Type / Status
Subject Susan Wojcicki E22723 entity
Predicate employer P7 FINISHED
Object YouTube E2481 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: YouTube | Statement: [Susan Wojcicki, employer, YouTube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YouTube
Context triple: [Susan Wojcicki, employer, YouTube]
  • A. YouTube chosen
    YouTube is a global online video-sharing and streaming platform where users can upload, watch, and interact with a vast range of video content.
  • B. YouTube Shorts
    YouTube Shorts is YouTube’s short-form vertical video platform designed for quick, snackable content similar to TikTok and Instagram Reels.
  • C. IGTV (discontinued as standalone brand)
    IGTV was Instagram’s long-form vertical video platform designed for creators to share extended, mobile-first video content beyond the standard feed and Stories.
  • D. YouTube Studio
    YouTube Studio is YouTube’s creator dashboard and management platform for uploading videos, tracking analytics, and managing channels.
  • E. YouTube freestyle platforms
    YouTube freestyle platforms are online channels and series where East Coast hip hop artists showcase improvised or unreleased verses, often emphasizing lyrical skill and authenticity.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b5312081909796df58fa7c1e9d completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66224db481909318add535721977 completed March 7, 2026, 5:53 p.m.
Created at: March 1, 2026, 7:42 p.m.