diff --git a/episodes/06-free-text.md b/episodes/06-free-text.md
index 4f705506..ebff8cde 100644
--- a/episodes/06-free-text.md
+++ b/episodes/06-free-text.md
@@ -352,7 +352,7 @@ And all this using a few commands on an otherwise unassuming but very powerful c
 - [The Command Line Crash Course](https://learncodethehardway.org/unix/). 'Learn UNIX the Hard Way' -- good for reminders of the basics.
 - [Automate the Boring Stuff](https://automatetheboringstuff.com/).
 - Another Coursera course, [Programming for Everybody (Python)](https://www.coursera.org/course/pythonlearn) is available and lasts 10 weeks, if you have 2-4 hours to spare per week. Python is popular in research programming as it is readable, relatively simple, and very powerful.
-- Bill Turkel and the Digital History community more broadly. The second lesson you did today was based on a lesson Bill has on [his website](https://williamjturkel.net/2013/06/15/basic-text-analysis-with-command-line-tools-in-linux/) and Bill is also a general editor of the [Programming Historian](https://programminghistorian.org/project-team). The Programming Historian is an open, collaborative book aimed at providing programming lessons to historians. Although the lessons are hooked around problems historians have, their lessons - which cover various programming languages - have a wide applicability - indeed today's course is based on two lessons I wrote with Ian Milligan, an historian at Waterloo, Canada - for ProgHist. Bill also has a wonderful tutorial on ['Named Entity Recognition with Command Line Tools in Linux'](https://williamjturkel.net/2013/06/30/named-entity-recognition-with-command-line-tools-in-linux/) which I thoroughly recommend if you want to automatically find, markup, and count names, places, and organisations in text files...
+- Bill Turkel and the Digital History community more broadly. The second lesson you did today was based on a lesson Bill has on [his website](https://web.archive.org/web/20260123211652/https://williamjturkel.net/2013/06/15/basic-text-analysis-with-command-line-tools-in-linux/) and Bill is also a general editor of the [Programming Historian](https://programminghistorian.org/project-team). The Programming Historian is an open, collaborative book aimed at providing programming lessons to historians. Although the lessons are hooked around problems historians have, their lessons - which cover various programming languages - have a wide applicability - indeed today's course is based on two lessons I wrote with Ian Milligan, an historian at Waterloo, Canada - for ProgHist. Bill also has a wonderful tutorial on ['Named Entity Recognition with Command Line Tools in Linux'](https://web.archive.org/web/20250923020615/https://williamjturkel.net/2013/06/30/named-entity-recognition-with-command-line-tools-in-linux/) which I thoroughly recommend if you want to automatically find, markup, and count names, places, and organisations in text files...
 
 ## Conclusion
 
@@ -366,8 +366,8 @@ Keep in mind that the full potential the tools can offer may only emerge upon em
 
 - James Baker and Ian Milligan, 'Counting and mining research data with Unix', *The Programming Historian* ([2014](https://programminghistorian.org/lessons/research-data-with-unix)).
 - Ian Milligan and James Baker, 'Introduction to the Bash Command Line', *The Programming Historian* ([2014](https://programminghistorian.org/lessons/intro-to-bash)).
-- William J. Turkel, 'Named Entity Recognition with Command Line Tools in Linux' ([30 June 2013](https://williamjturkel.net/2013/06/30/named-entity-recognition-with-command-line-tools-in-linux/)). The section 'NER Demo' is adapted from this and shared under a [Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-nc-sa/3.0/).
-- William J. Turkel, 'Basic Text Analysis with Command Line Tools in Linux' ([15 June 2013](https://williamjturkel.net/2013/06/15/basic-text-analysis-with-command-line-tools-in-linux/)). The sections 'Grabbing a text, cleaning it up' and 'Pulling a text apart, counting word frequencies' are adapted from this and shared under a [Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-nc-sa/3.0/).
+- William J. Turkel, 'Named Entity Recognition with Command Line Tools in Linux' ([30 June 2013](https://web.archive.org/web/20250923020615/https://williamjturkel.net/2013/06/30/named-entity-recognition-with-command-line-tools-in-linux/)). The section 'NER Demo' is adapted from this and shared under a [Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-nc-sa/3.0/).
+- William J. Turkel, 'Basic Text Analysis with Command Line Tools in Linux' ([15 June 2013](https://web.archive.org/web/20260123211652/https://williamjturkel.net/2013/06/15/basic-text-analysis-with-command-line-tools-in-linux/)). The sections 'Grabbing a text, cleaning it up' and 'Pulling a text apart, counting word frequencies' are adapted from this and shared under a [Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-nc-sa/3.0/).
 
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