Triple

T19879529
Position Surface form Disambiguated ID Type / Status
Subject Susan Wojcicki E477730 entity
Predicate employer P7 FINISHED
Object YouTube NE NERFINISHED

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. Dailymotion
    Dailymotion is a French video-sharing platform that allows users to upload, watch, and share videos, serving as an alternative to sites like YouTube and Vimeo.
  • C. Google Videos
    Google Videos was a video search and hosting service by Google that allowed users to upload, search, and view online video content before being largely superseded by YouTube.
  • D. Yahoo! Video
    Yahoo! Video was Yahoo's early online video hosting and streaming service that later evolved into the broader Yahoo! Screen platform.
  • E. YouTube Premieres
    YouTube Premieres is a YouTube feature that lets creators debut pre-recorded videos as live events with real-time chat and interactive viewer engagement.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658dd869c81908aed91ee767f5f3d completed April 20, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:52 p.m.