Triple
T9003437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messages |
E215087
|
entity |
| Predicate | supportsFeature |
P203
|
FINISHED |
| Object | Animoji |
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: Animoji | Statement: [Messages, supportsFeature, Animoji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Animoji Context triple: [Messages, supportsFeature, Animoji]
-
A.
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.
-
B.
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.
-
C.
FaceTime
FaceTime is Apple’s proprietary video and audio calling service that enables real-time communication across its devices and platforms.
-
D.
Live Photos
Live Photos is an Apple feature that captures a short moving image with sound around the moment a photo is taken, creating a brief, animated clip instead of a static picture.
-
E.
Face ID
Face ID is Apple's facial recognition system that securely unlocks devices and authorizes actions like payments and app logins using a 3D scan of the user's face.
- 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_69cc6957bd5481908ce74f32f8d197de |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e0a28c81909b6d2c6cd80e24d4 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.