Dungeon Crawler
Carl,
by the numbers

515 chapters
1,245,618 words
317 unique characters

This is what the entire crawl looks like when you slow down and count. A quantitative autopsy of Matt Dinniman's LitRPG masterpiece, powered by Enrich Reader's semantic text engine.

Entity mentions,
and how they shift

Watch entity counts grow and transition as Carl and Donut descent down the floors. The main characters lead early, but organizations, items, and events catch up in volume.

character location organization item event other
Vol. 1, Ch. 2
Playback Speed
Filter:

NLP extraction

The Carl Domination

Individual characters constitute the primary focus, but as the crawl expands, organizations, events, and game items grow rapidly, signifying the increasing complexity of the story.

52.8%

Top Entity Mentions Share

Narrative disappearances,
and absence spans

Discover the largest narrative gaps. The chart maps how many chapters a character completely disappears from the text before appearing again.

Longest narrative disappearance spans (chapters absent)

* Gaps represent segments where a character's name returns 0 mentions before their next appearance. Spoilers are hidden (no status or deaths are listed).

Series survival rate,
and the mortality feed

LitRPGs are brutal. Track the survival curve of characters introduced across the series. Watch the cumulative deaths increase as floors get more difficult.

Series Survival Curve (All Volumes)
Alive Dead
Series Mortality Feed ch. 2

Scrub timeline or press play to see character deaths feed live.

Lethal Chapter Ch. 13 (5 deaths)

How many
actually matter

Dungeon Crawler Carl has thousands of text lines, but NLP entity extraction filters noise. Track the funnel from total name mentions to unique characters, and see their distribution.

Vol. 1, Ch. 2
Playback Speed
4,280 raw mentions detected
317 unique characters

tracked across 1,245,618 words · 515 chapters

317 unique entities

Entity extraction filters narrative noise.

LitRPGs are filled with atmospheric noise—passing dungeon callouts, system announcements, short-lived mob names, and one-off side characters. By analyzing the narrative funnel, we see that only a fraction of detected names represent permanent characters. This quantitative layout demonstrates the power of Enrich Reader's core extraction pipeline to map the narrative spine of any manuscript.

Put data behind your narrative.

Are you an editor, literary agent, or self-published author? Enrich Reader's semantic intelligence engine extracts character arcs, presence gaps, and structural statistics to build interactive dashboards for your books.

Provide your EPUB or Word file for a free sample character timeline report.