Triple

T2703990
Position Surface form Disambiguated ID Type / Status
Subject PBS NewsHour E59298 entity
Predicate platform P1292 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: [PBS NewsHour, platform, YouTube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YouTube
Context triple: [PBS NewsHour, platform, 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. Vdio
    Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
  • C. .yt
    .yt is the country code top-level domain (ccTLD) assigned to Mayotte, an overseas department and region of France.
  • D. YouTube Shorts
    YouTube Shorts is YouTube’s short-form vertical video platform designed for quick, snackable content similar to TikTok and Instagram Reels.
  • E. YouTube Theater
    YouTube Theater is a modern, mid-sized indoor entertainment venue and performance space located in Inglewood, California, often used for concerts, award shows, and live events.
  • 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda518c58819096c8b67c0f754655 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf76caec8190930ead7931f7ea91 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.