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Will Weng: Overview, Related Topics & Entities

William C. "Will" Weng (February 25, 1907 – May 2, 1993) was an American journalist and crossword puzzle constructor who was the crossword puzzle editor for The New York Times from 1969 to 1977.

Language: English [EN]
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Will Weng topic overview

The analysis highlights Overview, Related Topics and Entities as prominent areas in the source structure around Will Weng.

Related topics
9
Source areas
1
Connected nodes
10
Extracted relationships
7
Concept neighborhoods
9
Bridge connections
10

What this topic covers Research coverage

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.

Overview · 9 topics

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.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Occupation
Crossword puzzle editor
Alma mater
Columbia University Graduate School of Journalism Indiana State University
Born
(1907-02-25)February 25, 1907 Terre Haute, Indiana, U.S.
Died
May 2, 1993(1993-05-02) (aged 86) New York City, U.S.
Employer
The New York Times
Predecessor
Margaret Farrar

Explore all related topics Closing gaps

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.

Overview

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Will Weng connects Entity context

The extracted context around Will Weng shows recurring relationship patterns in the source. For example, Will Weng → Columbia University Graduate School of Journalism Indiana State University Another extracted example is Will Weng → (1907-02-25)February 25, 1907 Terre Haute, Indiana, U.S.. Use these groups to spot repeated connection types before inspecting the individual relationships.

Will Weng

Top relations

Alma mater · 1
Will Weng → Columbia University Graduate School of Journalism Indiana State University
Born · 1
Will Weng → (1907-02-25)February 25, 1907 Terre Haute, Indiana, U.S.
Died · 1
Will Weng → May 2, 1993(1993-05-02) (aged 86) New York City, U.S.
Employer · 1
Will Weng → The New York Times
Occupation · 1
Will Weng → Crossword puzzle editor
Predecessor · 1
Will Weng → Margaret Farrar
Successor · 1
Will Weng → Eugene T. Maleska

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

crossword editor new york times weng puzzle farrar eugene maleska 1969 1977 born terre haute indiana state columbia university school

Will Weng relationships Subject–Predicate–Object triples

TTTA extracted 7 structured relationships around Will Weng. Examples in this analysis include Will Weng → Alma mater → Columbia University Graduate School of Journalism Indiana State University and Will Weng → Born → (1907-02-25)February 25, 1907 Terre Haute, Indiana, U.S.. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Will WengAlma materColumbia University Graduate School of Journalism Indiana State University1.00infobox
Will WengBorn(1907-02-25)February 25, 1907 Terre Haute, Indiana, U.S.1.00infobox
Will WengDiedMay 2, 1993(1993-05-02) (aged 86) New York City, U.S.1.00infobox
Will WengEmployerThe New York Times1.00infobox
Will WengOccupationCrossword puzzle editor1.00infobox
Will WengPredecessorMargaret Farrar1.00infobox
Will WengSuccessorEugene T. Maleska1.00infobox

Related concept clusters Concept neighborhoods

The concept neighborhoods around Will Weng bring nearby vocabulary together. In this analysis, examples include Puzzle, Crossword and Editor. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • crossword puzzle
    • Editor
    • New
    • Puzzle
    • Times
    • York
    • Farrar
    • Margaret
    • Eugene
    • Weng
    • Constructor
    • William
    • Born
  • the new york times
    • New
    • York
    • Puzzle
    • Crossword
    • Editor
    • Times
    • Columbia
    • Journalism
    • Margaret
    • School
    • University
    • Farrar
  • columbia university school of journalism
    • Journalism
    • School
    • University
    • Master's
    • Received
    • Times
    • Died
    • Haute
    • Indiana
    • Margaret
    • State
    • Terre
  • indiana state teachers college
    • College
    • State
    • Teachers
    • Terre
    • Haute
    • Indiana
    • Columbia
    • Died
    • Journalism
    • Margaret
    • School
    • University
  • terre haute, indiana
    • Indiana
    • State
    • Terre
    • College
    • Teachers
    • Columbia
    • Died
    • Journalism
    • Margaret
    • School
    • University
    • Eugene
  • margaret farrar
    • Farrar
    • Margaret
    • Eugene
    • Puzzle
    • New
    • Times
    • York
    • Died
    • School
    • State
    • Terre
    • University
  • eugene t. maleska
    • Farrar
    • Died
    • Haute
    • Indiana
    • Journalism
    • Margaret
    • School
    • State
    • Terre
    • University
    • Eugene
    • Maleska
  • Will Weng
    • Puzzle
    • Crossword
    • Editor
    • New
    • Times
    • York
    • American
    • Constructor
    • February
    • Journalist
    • May
    • William

Connections between topic areas Semantic bridges

Bridges highlight paths between different parts of the Will Weng map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Map overview Semantic statistics

Will Weng

Nodes11
Edges10
Triples7
Avg. degree1.82
Density0.181818
Components1

Source & methodology

TTTA analyzes the structure around Will Weng to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Overview, Related Topics & Entities, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Will Weng · EN edition · Analysis: TopicsToTalkAbout

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