Triple

T11160694
Position Surface form Disambiguated ID Type / Status
Subject Snap Inc. E264026 entity
Predicate product P490 FINISHED
Object Bitmoji E52239 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: Bitmoji | Statement: [Snap Inc., product, Bitmoji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bitmoji
Context triple: [Snap Inc., product, Bitmoji]
  • A. Bitmoji chosen
    Bitmoji is a popular app and feature that lets users create personalized cartoon avatars and use them as expressive stickers across messaging and social platforms.
  • B. Animoji and Memoji
    Animoji and Memoji are Apple’s animated, customizable characters that mirror a user’s facial expressions and are used in messaging and video calls on compatible Apple devices.
  • C. Moji
    Moji was a former city in Fukuoka Prefecture, Japan, that later became a ward of Kitakyushu and is known for its historic port and preserved retro district.
  • D. Kik
    Kik is a mobile instant messaging app that allows users to chat, share media, and interact with bots and services through a username-based platform.
  • E. Miquela
    Miquela is a feminine given name, commonly used in Spanish- and Portuguese-speaking cultures as a variant of Michaela or Michelle.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8817a90819087820d5241c58851 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4836718a08190b8eae87ce91bbfa0 completed April 19, 2026, 7:25 a.m.
Created at: April 8, 2026, 9:29 p.m.