Triple
T9003543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messages |
E215089
|
entity |
| Predicate | supportsFeature |
P203
|
FINISHED |
| Object | Memoji |
E215084
|
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: Memoji | Statement: [Messages, supportsFeature, Memoji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Memoji Context triple: [Messages, supportsFeature, Memoji]
-
A.
Bitmoji
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
chosen
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.
Niibo
Niibo was a former town in Niigata Prefecture, Japan, that later became part of the city of Sado through municipal merger.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6959497c8190a748c78504dd2eb6 |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd9bd544819083adf00db6a4a473 |
completed | April 3, 2026, 5:49 p.m. |
Created at: March 30, 2026, 7:05 p.m.