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Information Please is an American radio quiz show, created by Dan Golenpaul, which aired on NBC from May 17, 1938, to April 22, 1951. The title was the contemporary phrase used to request from telephone operators what was then called "information" and later called "directory assistance".
The analysis highlights Regulars, Accolades and International as prominent areas in the source structure around Information Please.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Information Please shows recurring relationship patterns in the source. For example, Information Please → Adams, After, CBS Television, Fadiman, James, John McCaffery, June, Kieran, Los Angeles, Michener, Musical Chairs, NBC Television, On August, September, Sundays, The, The Bill Leyden-hosted, The Fred Waring Show Another extracted example is Information Please → Albany, BearManor Media, Georgia, Martin Grams Jr. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
show program information radio please panel questions first nbc series question also sponsorship fadiman network panelists quiz would dan golenpaul
TTTA extracted 38 structured relationships around Information Please. Examples in this analysis include Information Please → Country of origin → United States and Information Please → Created by → Dan Golenpaul. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Information Please | Country of origin | United States | 1.00 | infobox |
| Information Please | Created by | Dan Golenpaul | 1.00 | infobox |
| Information Please | Genre | radio | 1.00 | infobox |
| Information Please | Network | NBC Radio | 1.00 | infobox |
| Information Please | No. of seasons | 13 | 1.00 | infobox |
| Information Please | Presented by | Clifton Fadiman | 1.00 | infobox |
| Information Please | Release | May 17, 1938 (1938-05-17) – April 22, 1951 (1951-04-22) | 1.00 | infobox |
| Information Please | Running time | 30 minutes | 1.00 | infobox |
| Information Please | is a | American radio quiz show | 0.90 | text |
| Information Please | related to External links | Radio IndexInformation Please | 0.60 | section |
| Information Please | related to External links | IMDbJerry Haendiges Vintage Radio | 0.60 | section |
| Information Please | related to External links | Logs | 0.60 | section |
The concept neighborhoods around Information Please bring nearby vocabulary together. In this analysis, examples include Please, Radio and Golenpaul. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Information Please, one of the stronger structural bridges in this analysis connects Information Please with Regulars. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Information Please to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Regulars, Accolades & International, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Information Please · EN edition · Analysis: TopicsToTalkAbout