Triple

T161270
Position Surface form Disambiguated ID Type / Status
Subject Web 2.0 E3289 entity
Predicate hasExample P1259 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: [Web 2.0, hasExample, YouTube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YouTube
Context triple: [Web 2.0, hasExample, 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. YouTube Studio
    YouTube Studio is YouTube’s creator dashboard and management platform for uploading videos, tracking analytics, and managing channels.
  • D. YouTube Stories
    YouTube Stories was a short-form, ephemeral video format on YouTube that allowed creators to share temporary, mobile-first content similar to Instagram and Snapchat stories.
  • E. YouTube TV
    YouTube TV is a subscription-based live TV streaming service that offers access to major broadcast and cable channels over the internet.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25856d934819095460b2ea566eb6b completed Feb. 28, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2d4cbaedc81908aa7cf4df2661ccc completed Feb. 28, 2026, 11:43 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.