Triple

T2412955
Position Surface form Disambiguated ID Type / Status
Subject Evan Spiegel E52235 entity
Predicate coFounded P104 FINISHED
Object Snapchat E52237 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: Snapchat | Statement: [Evan Spiegel, coFounded, Snapchat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snapchat
Context triple: [Evan Spiegel, coFounded, Snapchat]
  • A. Snapchat chosen
    Snapchat is a multimedia messaging and social media app known for its disappearing photos and videos, creative filters, and Stories feature popular among younger users.
  • B. Snap Camera
    Snap Camera is a desktop application by Snap Inc. that lets users apply Snapchat-style augmented reality lenses and filters to their webcam video for use in video calls and streaming.
  • C. Periscope
    Periscope was a live video streaming mobile app that allowed users to broadcast and watch real-time video from around the world.
  • D. WeChat
    WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
  • E. Burbn
    Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc92a4e1c8190819fa676295ac145 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3f00cc481909c2841a6f2ebadad completed March 9, 2026, 11:50 a.m.
Created at: March 6, 2026, 9:41 p.m.