Triple
T13551952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shouts & Murmurs |
E323668
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Condé Nast |
E166295
|
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: Condé Nast | Statement: [Shouts & Murmurs, publisher, Condé Nast]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Condé Nast Context triple: [Shouts & Murmurs, publisher, Condé Nast]
-
A.
Condé Nast
chosen
Condé Nast is a major global media company known for publishing influential magazines such as Vogue, The New Yorker, GQ, and Wired.
-
B.
Time Inc.
Time Inc. was a major American media company best known for publishing influential magazines such as Time, Life, Sports Illustrated, and Fortune.
-
C.
Hearst Magazines
Hearst Magazines is a major American magazine publisher known for producing a wide range of popular consumer titles across lifestyle, fashion, home, and entertainment categories.
-
D.
Hearst Magazines International
Hearst Magazines International is the global publishing division of Hearst that licenses and distributes many of the company’s major magazine brands in international markets.
-
E.
Hearst
Hearst is a small, predominantly Francophone town in northern Ontario, Canada, known for its forestry industry and strong French-Canadian cultural presence.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaff0a6548190b8cde5084cef0061 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75da721208190a3f5159125dbde9a |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:46 p.m.