Triple
T1880600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harper’s Bazaar |
E39843
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Hearst Magazines |
E37938
|
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: Hearst Magazines | Statement: [Harper’s Bazaar, publisher, Hearst Magazines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hearst Magazines Context triple: [Harper’s Bazaar, publisher, Hearst Magazines]
-
A.
Condé Nast
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 Communications
chosen
Hearst Communications is a major American mass media and business information conglomerate with interests in television, cable networks, magazines, newspapers, and digital media.
-
D.
Hearst
Hearst is a small, predominantly Francophone town in northern Ontario, Canada, known for its forestry industry and strong French-Canadian cultural presence.
-
E.
Frank A. Munsey Company
Frank A. Munsey Company was an American publishing firm best known for pioneering pulp magazines and mass-market fiction in the late 19th and early 20th centuries.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0fa3d388190993073ffb0f60a84 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeae44f6c8190a5924609863030a4 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:34 p.m.