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Max Perlich: Career, Early life & Overview

Max Perlich (born March 26, 1968) is an American film and television actor. In 1990, Perlich won the Independent Spirit Award for Best Supporting Male for his performance in the hit indie film Drugstore Cowboy and was nominated for the same award in 1996 for his performance in Georgia.

Language: English [EN]
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Max Perlich topic overview

The analysis highlights Career, Early life and Overview as prominent areas in the source structure around Max Perlich.

Related topics
42
Source areas
3
Connected nodes
45
Extracted relationships
14
Related term clusters
15
Bridge connections
45

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.

Career · 30 topics
Early life · 9 topics
Overview · 3 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
Actor
Born
(1968-03-26) March 26, 1968 (age 58) Cleveland, Ohio, U.S.
Spouse
Jia Mae
Years active
1986–present

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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

Early life

Career

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Max Perlich connects Entity context

The extracted context around Max Perlich shows recurring relationship patterns in the source. For example, Max Perlich → (1968-03-26) March 26, 1968 (age 58) Cleveland, Ohio, U.S. Another extracted example is Max Perlich → Actor. Use these groups to spot repeated connection types before inspecting the individual relationships.

Max Perlich

Top relations

Born · 1
Max Perlich → (1968-03-26) March 26, 1968 (age 58) Cleveland, Ohio, U.S.
Occupation · 1
Max Perlich → Actor
Spouse · 1
Max Perlich → Jia Mae
Years active · 1
Max Perlich → 1986–present

Important terminology

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

Important terminology

perlich television film born cleveland max georgia actor ohio girls also hit drugstore cowboy 1996 life career 1986 roles gilmore

Max Perlich relationships Subject–Predicate–Object triples

TTTA extracted 14 structured relationships around Max Perlich. Examples in this analysis include Max Perlich → Born → (1968-03-26) March 26, 1968 (age 58) Cleveland, Ohio, U.S. and Max Perlich → Occupation → Actor. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Max PerlichBorn(1968-03-26) March 26, 1968 (age 58) Cleveland, Ohio, U.S.1.00infobox
Max PerlichOccupationActor1.00infobox
Max PerlichSpouseJia Mae1.00infobox
Max PerlichYears active1986–present1.00infobox
Superstoreinstance ofknown for her roles in shows0.80text
Gilmore Girlsinstance ofknown for her roles in shows0.80text
and his fatherinstance ofknown for her roles in shows0.80text
Martin Perlichinstance ofknown for her roles in shows0.80text
was a writerinstance ofknown for her roles in shows0.80text
radio programming directorinstance ofknown for her roles in shows0.80text
announcerinstance ofknown for her roles in shows0.80text
who worked for a time with the Cleveland Orchestrainstance ofknown for her roles in shows0.80text

Related concept clusters Related term clusters

The concept neighborhoods around Max Perlich bring nearby vocabulary together. In this analysis, examples include Perlich, American and March. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Max Perlich
    • Perlich
    • American
    • March
    • Career
    • Cleveland
    • Hit
    • Actor
    • Born
    • Film
    • Television
    • Award
    • Best
  • max perlich
    • Perlich
    • American
    • March
    • Career
    • Cleveland
    • Hit
    • Actor
    • Born
    • Television
    • Film
    • Award
    • Best
  • martin perlich
    • Career
    • Cleveland
    • Hit
    • Television
    • Award
    • Best
    • Independent
    • Ohio
    • Spirit
    • Supporting
    • Won
    • Began
  • drugstore cowboy
    • Cowboy
    • Drugstore
    • Independent
    • Spirit
    • Supporting
    • Won
    • Appearing
    • Began
    • Films
    • Georgia
    • Hit
    • Lost
  • independent spirit award for best supporting male
    • Award
    • Best
    • Independent
    • Spirit
    • Supporting
    • Won
    • Cowboy
    • Drugstore
    • Georgia
    • Hit
    • Film
    • Perlich
  • georgia
    • Independent
    • Spirit
    • Supporting
    • Won
    • Films
    • Hit
    • Lost
    • Also
    • Girls
    • Perlich
  • gilmore girls
    • Roles
    • Girls
    • Also
    • Appearing
    • Recurring
    • Series
    • Films
    • Lost
    • Television
    • Perlich
  • beautiful girls
    • Roles
    • Also
    • Appearing
    • Films
    • Lost
    • Recurring
    • Series
    • Television
    • Perlich

Connections between topic areas Semantic bridges

For Max Perlich, one of the stronger structural bridges in this analysis connects Max Perlich with Career. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Max Perlich — Career · splits 15 ⟂ 31
Max Perlich — Early life · splits 36 ⟂ 10
Max Perlich — Overview · splits 42 ⟂ 4

Map overview Semantic statistics

Max Perlich

Nodes46
Edges45
Triples14
Avg. degree1.96
Density0.043478
Components1

Source & methodology

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

Source: Wikipedia — Max Perlich · EN edition · Analysis: TopicsToTalkAbout

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