Triple
T1935530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notification Center |
E41434
|
entity |
| Predicate | notificationSource |
P409
|
FINISHED |
| Object |
E41444
|
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: Mail | Statement: [Notification Center, notificationSource, Mail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mail Context triple: [Notification Center, notificationSource, Mail]
-
A.
Mail
chosen
Mail is Apple’s built-in email client application for macOS, used to send, receive, and manage email accounts.
-
B.
InMail
InMail is LinkedIn’s premium messaging tool that lets users directly contact other members they’re not connected with on the platform.
-
C.
Mailbox
Mailbox was a popular mobile email management app known for its innovative swipe-based interface and focus on inbox organization, later acquired by Dropbox.
-
D.
Messenger
Messenger is Meta's cross-platform messaging application that enables users to send text, voice, and video communications across mobile and web.
-
E.
Mailer
Mailer is a surname most notably associated with American novelist, journalist, and essayist Norman Mailer.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb7c51c2881908054760c624dd577 |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbb52d04819097c3df9691551aaa |
completed | March 8, 2026, 10:44 p.m. |
Created at: March 4, 2026, 7:35 p.m.