Triple
T2620629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Mailer |
E58998
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Mailer |
E58998
|
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: Mailer | Statement: [Norman Mailer, hasSurname, Mailer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mailer Context triple: [Norman Mailer, hasSurname, Mailer]
-
A.
Mailer
chosen
Mailer is a surname most notably associated with American novelist, journalist, and essayist Norman Mailer.
-
B.
Mail
Mail is Apple’s built-in email client application for macOS, used to send, receive, and manage email accounts.
-
C.
SMTP
SMTP (Simple Mail Transfer Protocol) is a standard communication protocol used for sending and routing email messages across IP networks.
-
D.
Media Mail
Media Mail is a discounted U.S. Postal Service shipping option specifically for sending educational materials and media such as books, sound recordings, and DVDs.
-
E.
InMail
InMail is LinkedIn’s premium messaging tool that lets users directly contact other members they’re not connected with on the platform.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd897acb481909a976b70304cc30e |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98b50fa08190abe65b53081cb06b |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:50 p.m.