Triple
T10764165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanenbaum–Torvalds debate articles |
E253909
|
entity |
| Predicate | platform |
P1292
|
FINISHED |
| Object | Usenet |
E233830
|
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: Usenet | Statement: [Tanenbaum–Torvalds debate articles, platform, Usenet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Usenet Context triple: [Tanenbaum–Torvalds debate articles, platform, Usenet]
-
A.
Usenet
chosen
Usenet is a worldwide distributed discussion system that predates the modern web, where users post and read messages in topic-based newsgroups.
-
B.
NNTP
NNTP (Network News Transfer Protocol) is an application-layer protocol used for reading and posting articles on Usenet newsgroups over TCP/IP networks.
-
C.
UUCP
UUCP (Unix-to-Unix Copy Program) is an early suite of computer programs and protocols used primarily on Unix systems to transfer files, email, and netnews between computers over serial lines and dial-up connections.
-
D.
BBS
BBS is the station code used to identify the Brandenburger Tor S-Bahn station in Berlin’s public transit system.
-
E.
Gnus
Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a504948190943f0e27c0d891ed |
completed | April 9, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de235fe7748190ba004f889da389ff |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.