At the end of the new edition of Discovering English with VersaText, published yesterday, there is a list of 22 takeaways. These are the points that I hope I have instilled in the readers. They embrace teaching, learning, creativity, metalinguistics, metacognition (all things meta TBH), guided discovery, text, grammar, vocabulary, pronunciation, depth, respect and colour.

Here they are.

1. Text is the starting point.
2. The multiple affordances of texts and tasks.
3. The Six Pillars of Vocabulary – the properties of words.
4. All properties of words beget language learning tasks.
5. The task activates learning.
6. Relationships between words carry meaning.
7. Relationships between words and grammar carry meaning.
8. Disabuse students of the idea that vocabulary is random.
9. Reveal the visible patterns in language – patterns of normal usage.
10. Respect students' intelligence.
11. Students benefit from guided discovery.
12. Flatter students' intelligence by introducing terminology and its etymology.
13. Tell students the truth or lead them to discover it.
14. Train students in the art and science of observation and pattern hunting.
15. Take students on the journey from analysis to synthesis.
16. Prepare students to become lifelong learners.
17. Let them bask in the wonder of meaning creation.
18. Demystify English at all levels of the Hierarchy of Language.
19. Accept that students have to do the learning and teachers have to lead them to finding their own optimal paths.
20. Equip students with the information and skills they need to make guided discovery work for them.
21. Don't accept students' narrow view of language as a foundation for their wish list when asked what they would like to do or like to learn.
22. Never stop asking students, HDYK.

Originally, a Kindle only, it is now also a print book with white space for readers' answers, notes, comments. The new edition reflects all the updates we have made to the free, online software, and AI appears at pertinent moments.
The Kindle and book are available from Amazon.

​Should you be interested in all things VersaText, or even some of them, feel free to join the Facebook group too.

Language learners benefit greatly from example sentences, since it is an opportunity to learn language from language, my big thing. For this reason, I devoted a considerable amount of my teaching, training and writing to helping students gain the maximum benefit from illustrative sentences.

In the early 2000s, I attended my first Teaching and Language Corpora conference in Bertinoro, a beautiful hilltop town near Bologna, and presented my incipient formula for computationally selecting the most useful sentences from corpora to present to students. I programmed a tool that allocated the frequency of every word in a sentence and average it. Sentence length was also a criterion.

As mentioned in previous posts, the great English lexiocagrapher, Patrick Hanks was my colleague at this time and I asked him what criteria his kind used when selecting sentences to include in their dictionaries. He said there was no list.

I worked on this further and came up with a list of ten criteria that I discussed with Patrick and he added one more. I gave this list to Pavel Rychlý, who was developing Sketch Engine and his team used these criteria as a basis for their GDEX algorithm, i.e. good example sentences. It is now a standard part of SkELL and Sketch Engine. My criteria are listed on this 2006 webpage.

So, it’s a good thing that corpora can select illustrative sentences, but can students? And should they? In short, yes and yes. But then what? How does a learner know what they can learn from an illustrative sentence apart from it being a targeted piece of input which they might soak in, as they do from any input they are exposed to. The answer lies in knowing the properties of the target word that are necessary to shift it from active to passive use.

I am a strong advocate of the Collins COBUILD Advanced Learner’s Dictionary because it even presents its definitions in full sentences. Full sentence definitions are goldmines. From the sentence defintion, you can easily extract concept checking questions (CCQs). For example,

Collins: A wildcard is a symbol such as * or ? which is used in some computing commands or searches in order to represent any character or range of characters.

• What is a wildcard? A symbol
• What are some examples of wildcard? * or ?
• Where is it used? In computing commands
• What is its function? to represent any character …

Collins: An aphorism is a short witty sentence which expresses a general truth or comment.

• What is an aphorism? a short witty sentence.
• What does it do? it expresses a general truth or comment.

These sentences typically start with a hypernym, here symbol, which immediately limits what it is and is not. Their definitions progress with the target word’s features, functions, etc. Each of these is encapsulated in a phrase or clause in the sentence definition. They are the properties of the word. The Collins then provides example sentences in which the abstract properties are made concrete. If students know what they can learn from full sentence definitions, they can see how the meanings of words manifest in authentic sentences.

I’m writing a student workbook at the moment which will probably be called Discovering Phrasal Verbs, in which students are repeatedly tasked with finding example sentences in corpora. The book explains the importance of the semantics of the phrasal verb particles (prepositions and adverbs) and the importance of the subjects and objects of the verbs. These properties are the most important contributors to the meanings of the otherwise opaque, or at best translucent, phrasal verbs.

When you search corpora for a phrasal verb, the sheer volume of data can be overwhelming. Fortunately, SkELL uses GDEX, so the 40 sentences it presents are manageable. The other tool I recommend is CorpusMate because it is very fast, it enables searches with wildcards, and the cotext is colour-coded using the same colours for parts of speech as VersaText. The wildcard searches are necessary when the phrasal verb is separable, e.g. tear .* away, keep .* .* away.
​

AI is another source of illustrative sentences. In ChatGPT's own words, "The sentences generated by AI are original constructs, created using the language patterns learned during training." They are by definition inauthentic sentences, which means they were not motivated by any communicative impetus, hence they lack real-world contexts. These sentences often resemble those made up by textbook authors and test creators. It is reasonable to ask if the trade-off between authentic and inauthentic example sentences in terms of learnability is worth it. Do students really benefit more from authentic than inauthentic sentences?
​
Like all good questions in ELT, the answer starts with, it depends. My it depends revolves around what the students are tasked with. If the textbook provides made-up example sentences without any task other than perhaps read, read aloud, translate or memorise some sentences, the students will function at the bottom of Bloom's Taxonomy. Garbage in, garbage out.

​But if the tasks involve higher order thinking skills in which the students skim and scan multiple examples of authentic language in search of specific properties to which they have been alerted, they develop a better understanding of the properties of the target word, and ultimately a more sophisticated understanding of language per se emerges. Like all good citizen-scientists, students engaged in “extreme noticing” need systems to record their findings that will in turn deepen their conceptual grasp of the target language and prepare them to use it confidently.

It is well-known that guided discovery is not for everyone. I was a school music teacher in my 20s and one would occasionally hear, Never try to teach a pig to sing: it wastes your time and annoys the pig. This is yet another aphorism attributed to Mark Twain, but who knows?
​
Guided discovery demands a strong rationale, clear instructions, the right tools and an understanding that the students are going to benefit from the multiple affordances of the tasks. It is important that students are made aware of the multiplicity of these learning experiences in the process of acquiring words and their properties. No reflection, no connection.

​Max’s podcasts are mostly targeted at B1 level, and since his work is partly motivated by Krashen’s comprehensible input hypothesis, I listen for gist. My Russian is well below B1 but I comprehend a lot, and could probably retell the thrust of his monologues in English. This is thanks to my study of Russian, its closeness to Czech and its vocabulary having many English and international words, including those that have Greek and Latin origins. I should mention that there are many false friends between Russian and Czech, my favourite being užasný (amazing, awesome) vs. ужасный (terrible).

Each of Max’s podcasts revolve around a single topic, so there is always the general context to help with the gist, but since he only speaks Russian in the podcasts, you have to infer the topic as well. There is no time during the podcast to analyse his use of words so that you might be able to use them in the cotexts that he employs. It is challenging to observe collocation, colligation and chunks on a single listening, and it is not why we listen.
 
So, while the gym has a leg abduction machine, I would say that our brains have a language abduction machine. Abductive reasoning is a form of logical inference that seeks the simplest and most likely conclusion from a set of observations. We do a lot of abducting when our comprehensible input is only just comprehensible.
 

Our word knowledge typically emerges over time in both first and second language acquisition contexts. In FLA our word knowledge mainly accrues through multiple exposure, although we do use dictionaries, chat to friends about new and surprising uses of words. We even read and watch videos about language. In SLA, our word knowledge mainly accrues through structured study, which is both motivated and reinforced by exposure as we read, write, speak and listen.
 
The emergent stages of vocabulary competence can be described thus:

​I am devoting some pages to flashcards, the use of AI, and this continuum in the book I am writing at the moment. It might have the bumptious title, How to Learn Vocabulary Properly. We’ll see! 

​Hoey in fact studied foreign languages so that he could experience the processes of language learning and the practical applications of linguistic and pedagogical theory. When he was observing language in context, that is by reading and listening, he would notice certain collocations but he needed proof of their typicality before he could consider them worth learning. Just because someone has combined a pair of words does not mean that this combination is a typical formulation in the language. The lexicographer, Patrick Hanks (1940–2024) felt the same: Authenticity alone is not enough. Evidence of conventionality is also needed (2013:5).

Some years before these two Englishman made these pronouncements, Aristotle (384–322 BC) observed that one swallow does not a summer make. Other languages have their own version of this proverb, sometimes using quite different metaphors, but all making the same point.

​In order to ascertain that an observed collocation is natural, typical, characteristic or conventional, it is necessary to hunt it down, and there is no better hunting ground for linguistic features than databases containing large samples of the language, a.k.a corpora. In the second paragraph, Hoey experienced the processes … Is experience a process a typical collocation? This is the data that CorpusMate yields:

In the same paragraph, we have the following collocation candidates:

• study language
• foreign language
• apply theory
• observe language
• notice collocation
• combine words
• typical formulation

Here is some more data from CorpusMate.

In the following example, we have a wildcard which allows for one element to appear between the two words of the collocation. Even in these first 12 of the 59 results, other patterns are evident.

The process of validating your findings through multiple sources or methods is known as triangulation, and it is an essential stage in most research. When we train students to triangulate their linguistic observations, it is quite likely that they are familiar with this process from their other school subjects.

This is not just a quantitative observation, i.e. this collocation occurs X times in the corpus. It is qualitative as well: the students observe other elements of the cotext, such as the use of other words and grammar structures that the collocation occurs in. They might also observe contextual features that relate to the genres and registers in which the target structure occurs.

They are being trained in task-based linguistics as citizen scientists, engaging their higher order thinking skills as pattern hunters. This metacognitive training is a skill for life that will extend far beyond the life of any language course they are undertaking.

Triangulation does not apply only to collocation. Any aspect of language can be explored in this way. You may have noticed the word order in the idiom: does not a summer make. Many people have run with this curious word order and exploited it creatively. It is thus a snowclone. Here are some examples from SkELL.

Respect our students' intelligence and ​equip them to learn language from language.

Croswaithe, P. & Baisa, V. (2024) A user-friendly corpus tool for disciplinary data-driven learning: Introducing CorpusMate International Journal of Corpus Linguistics.
    
Hanks, P. (2013) Lexical Analysis: Norms and Exploitations. MIT.
​
Hoey, M. (2000) A world beyond collocation: new perspectives on vocabulary teaching. Teaching Collocation. Further Developments in the Lexical Approach. LTP (ed. Lewis, M.)

• warm and fuzzy
• furry and fuzzy
• cuddly and fuzzy
• cute and fuzzy.

None of these eight combinations occur frequently enough in SkELL's billion word corpus to be anointed chunks. English can certainly boast many very high frequency “and” chunks, such as:

• first and foremost
• tried and tested
• doom and gloom
• chalk and talk
• part and parcel
• pen and paper
• trials and tribulations.

With their poetic alliteration and their internal rhyming scheme, these are chunks with their own semantic and pragmatic functions in the language.

Our fuzzy examples, however, are properties of the word. Make a word sketch for pretty much any noun, verb, adjective, or adverb in the English language and you will find words that and links it with. The more arcane the word, the more arcane the partners. See arcane, for example.

Search for words that are in a text you are studying or on a word list you are working with. Explore the "and" relationship by clicking on a word to see it in sentence examples. For example, in the "and" relationship of class, we see among others:

• gender
• category
• method.

Clicking on gender shows 40 example sentences that include class and gender. This must be more than a lexical relationship – it is cultural and political.

Clicking on category shows 40 sentences related to categorisation. Once again, this represents the way this topic is written and spoken about.

Remember that we do not need to read and grasp the sentence examples that corpus searches yield. A concordance page is not a text – it is a source of language data that we skim and scan to identify patterns of normal usage from which we learn how the language works so that our use of the foreign language approximates that of the many native speakers whose output has turned up in the corpus.

The "and" pattern, connecting two words of the same part of speech and with similar semantics, often offers lexical support. Rather than expressing something new, this quasi repetition reinforces the meaning or general impression being communicated. This is particularly noticeable with subjective and emotive words. Look at the "and" relationships of:

• angry
• funny
• modest

There is also the matter of word order. Words in these and relationships are usually said in a set order.

• Coffee and tea is much less frequent than tea and coffee.
• Compare and contrast vs. contrast and compare.
• When and where vs. where and when.
• Reading and writing  vs. writing and reading.

As language teachers and speakers of foreign languages, we are always interested in the properties of words. Knowing a word’s patterns of normal usage is key to using words as native speakers do. And the confidence that emerges from this knowledge impacts on fluency.

I had an email from a teacher who loves using my VersaText tool with his students. In addition to the very welcome and rarely received praise for VersaText, he was enquiring into the possibility of adding a collocation feature. As you know, VersaText works with single texts, its slogan being, “learning language from language, one text at a time”, collocations are vanishingly rare. In fact, “vanishingly rare” is a strong collocation in English. Check out the examples in #SkELL.

#Collocation is defined variously. First and foremost, collocation consists of two content words of different parts of speech. Compound nouns and adjectives, phrasal and delexical verbs are not collocations. And neither are words that combine with that/ -ing / inf / wh-/prepostions. These are colligations and offer very little choice, if any. You’ve all seen gap fills in coursebooks and exams that test this. Collocation does permit some variation, but within limits of acceptability if you are going to use the patterns of normal usage of the language.

One category of definitions of collocation revolves around statistical frequency. These definitions rely on the number of times words occur in close proximity to each other. The verb collocates of trouble, for example, occur frequently within four words before and/or after the noun in SkELL's huge sample of English.

Other definitions of collocation are phraseological: cause trouble is the core of a clause, which is the essential structure that creates Messages, which in turn constitutes text. Up the Hierarchy of Language we go! 

Most key words in most texts collocate with different items because the author is telling us something new about the word. And this is why a collocation tool in VersaText would be by and large redundant.
​
One thing we can be sure of in a text is that the author is not going to repeat the same message repeatedly, again and again, over and over, unless they have some rhetorical reason for doing so.  Here is an example. In VersaText’s sample text, Learning Zone (a transcript of a TED Talk), we see that the verb spend is frequently used with time, and with other time words, e.g. minutes, hours, our lives. It occurs 13 times in the text. Time occurs 28 times in the text and is used thus: ​

Go to VersaText, select the Learning Zone text from the list, then click Wordcloud at the top. If you want the lemma of improve, for example, choose the lemma radio button under the word cloud. Click on any word to see its concordance in this text. This motivates many discovery learning tasks for the students.

If you want to learn more about studying and teaching English with VersaText, click the Course button at the top of the VersaText pages.

My phraseological approach to collocations in single texts is the Word Constellation. See my blog post linked below. 

So, how many words are in this sentence?

• During the fight, each combatant attempts to strike at the enemy without being struck.

Did you count strike and struck as one word or two? Did you count the twice?

If our definition of a word is a string of letters surrounded by a space or punctuation, it is the same as our computer’s word counts. These are known as orthographic words. We count strike and struck as two word forms of the lemma strike.  The other word forms are strikes, striking, stricken.

We can distinguish tokens - the number of orthographic words  in a sentence or text from types - the number of different word forms. 

In the next sentence, strike is a noun and a verb. This is variously known as conversion and zero derivation. These are different lemmas – a lemma is the set of word forms of one part of speech.  The noun lemma is strike, strikes. 

• The flight attendants ended their strike the following day, but the others continued to strike.

Is flight attendant one word or two? In the next sentence, we have a phrasal verb and a compound adjective. 

• The guys who never strike out much have the best two-strike approach.  ​

​
The two orthographic words create these lexemes, i.e. units of meaning. Lexemes can be single words or compounds. Flight attendant is a compound noun, i.e. a lexeme. It is not a collocation because the two words in a collocation retain their individual meanings, e.g. end strike in the second sentence and good approach in the third – best being part of the lemma ​good.

The set of word forms that are formed from a single word are a word family. If you fill the Taxonomy of Morphology with all the word forms of strike, you will have depicted its word family. In addition to the word forms of strike we have already seen, it might include misstrike, overstrike, outstrike, pre-strike, re-strike, strikeout, strike-through, striker, striking (adj), strikingly.

This may seem like a lot of trouble to go to to answer a question about the number of words in a sentence. In fact, counting words is just a task that draws attention to the issue. Having a superior conceptual grasp of “word” allows students to complete the Taxonomy of Morphology for any lexical items they are studying. Ideally they would observe them whilst reading, listening and watching and add them to their stunningly visual or visually stunning vocabulary notebooks. This would be the impetus for seeking out more word forms of a target word. ​

Halliday considered the term lexical item less indeterminate than the folk-definition of word as he called it. Our students deserve more than the folk definition. They don’t have folk definitions of concepts of physics, chemistry, biology, literary devices and other conceptual networks that they study at secondary school and beyond. They don’t even have folk definitions of the passive voice, articles, conditionals, subordinate clauses and other grammatical concepts when learning English. Their knowledge of vocabulary is however profoundly superficial.
​
We are not helping our students develop their active vocabulary if they cannot distinguish a collocation from a compound noun, if they do not know the properties of phrasal verbs and delexical verb structures, if they do not know that the relationship between vehicle, car and sedan is systematic, if they are unaware of the patterned use of prepositions with nouns, verbs and adjectives as comprehensively demonstrated in these two books from COBUILD. ​

Their higher order thinking skills are also being exercised when they annotate vocabulary features of whole texts. They can trace the topic trails, the different uses of repeated keywords, the collocations and colligations that the author has used. When the students are engaged in wide reading and observe patterns in the use of key words in CLIL, ESP, EMI or general English projects, they learn their genre and register specific usages. This plays a significant role in acculturating students into the conceptual and linguistic milieu of their field. 
​
Only students can learn vocabulary. Teachers can teach them about vocabulary and provide them many vocabulary learning strategies, many of which depend on an awareness of lemmas and lexemes, types and tokens, collocation and colligation, word templates and topic trails. And the rest! There is much to be done.

​

Having been engaged in language study for over four decades, made attempts on four foreign languages and witnessed the growth of my first language, English, I can assure you that I have invested a great deal of time into learning vocabulary. Much of it was wasted. Much of it was spent learning useless words in ways that did not teach me how the words work in the target language. Vocabulary learning strategies were not taught. It was simply assumed that students would memorise context-free bilingual lists as if the L2 words worked in the same way as in L1. If I was lucky, my attempts to use the words in sentences and texts were returned bespattered with red ink highlighting collocation and colligation errors in particular. ​

You can probably think of some counter examples. And so can I. But what I see in contemporary course books does not negate most of the above. ​

We can task our students with identifying relationships between words and within words, and depict them meaningfully. 

These examples come from my Versatile Blank Book, which you can read about on this site.

Every layer of the hierarchy of language can be explored by students in a text. The exploration of Texts as Linguistic Objects (TALO) reveals how an author has used words and word forms, combined them as collocations and colligations, formed phrases and clauses that are linked with metadiscourse chunks to ultimately form texts. This is the bottom-up process that we employ both subconsciously and consciously when we speak and write. ​

As well as being linguistic objects, Texts are also Vehicles of Information (TAVI) which invoke top-down processes as we combine the content of the text with what we know about the world through schemata, general knowledge and our expectations of text types. In this way, readers and listeners are engaged in their own personal knowledge creation. 

Thirdly, Texts are Springboards for Production (TASP). We respond to texts by combining several texts on the same topic, by critiquing aspects of the text, and by discussing the potential impact of this new knowledge, for example.

To put texts under the microscope, VersaText is an open access, web-based resource that allows teachers and students to paste in a single text. The program provides several tools that foster discovery learning. The first tool is the word cloud, which depicts not only the relative frequencies of words in a text, but it colour-codes part of speech. The word cloud is highly customisable: the number of words, the choice of words vs. lemmas, which parts of speech to show. The relative sizes of words in the word cloud illustrate the extent of repetition in a text and repetition is the most commonly used resource to create lexical cohesion in text (Halliday & Hasan, 1976).​

The opportunity to put the language of a single text under such a microscope is invaluable to students of CLIL, EMI and ESP, as the texts are models of the language of subjects and fields that the students need to have a productive knowledge of, if they are to be acculturated into their subject disciplines. This is essential for TASP. 
​

Halliday, M.A.K. & Hasan, R. (1976) Cohesion in English.  Longman
Hoey, M. (1991) Patterns of Lexis in Text. OUP.
Johns, T., Davies, F. (1983) Text as a vehicle for information: the classroom use of written texts in teaching reading in a foreign language. Reading in a Foreign Language, 1 (1)
Partington, A. (1998) Patterns and Meanings: Using Corpora for English Language Research and Teaching.    John Benjamins.

In my last blog post, "…", I wrote:

• When we search a corpus for "does not a .* make", it is clear that this is a systematic linguistic exploitation, as the great British lexicographer, Patrick Hanks refers to such creative uses of language. 

Since I wrote this, this great British lexicographer has passed away.
 
Patrick's theory was articulated in his unputdownable book Lexical Analysis: Norms and Exploitations (2013). It is an empirical investigation into how words go together in collocation patterns and constructions to make meanings. In the book he writes extensively about patterns of normal usage and then demonstrates how a great deal of creative language use is also patterned, albeit differently. By the time Lexical Analysis was published, I had known Patrick for quite a while during our overlapping years at the Faculty of Computer Science (FI MU Brno). Our offices were on opposite sides of a corridor across which we'd often call to each other.

​Patrick had not been fully apprised of the doctoral defence procedure. Czech doctoral defences are preceded by an oral exam and he more or less delivered his inspired defence during the exam. We had to wait outside the exam room while the committee determined his exam result before allowing him to give his defence, which turned into a grand round table discussion. I remember James Pustejovsky, who'd been flown from the USA for the defence, ramping up Patrick's interrogation by claiming that he was getting off a little bit lightly. He passed.

Before the New Oxford, there was the COBUILD project at Birmingham University in the 1980s. Patrick was the managing editor of the COBUILD Dictionary. I distinctly remember the day he strode the metre and a half from his office to mine to tell me that he'd just learnt of the death of his dear friend and colleague, John Sinclair. Sinclair had run the highly innovative COBUILD project for a decade. Patrick would often relate the day Sinclair announced to his team of lexicographers that all of the dictionary's definitions would be written in full sentences unlike the standard practice of providing synonyms and snippets to express a word's meaning. These sentence definitions are built up of chunks of information that explain what and why and how something means what it means. This aspect of the COBUILD dictionary is why I recommend it to students and teachers in all my training and writing. I shall wax lyrical on this in another post.
 
One Friday afternoon, Patrick drove around the corner from the faculty to the bank, unnecessarily and lamentably. He came back from the bank on foot, his car having been stolen. Unfortunately, he hadn't finished unloading boxes of rare and specialist books from his car into the flat that a friend of mine let to him. The police came and drove Patrick and me around the neighbourhood for quite some time before they took us to the police station where we spent hours answering questions for the policeman to fill in forms. I was interpreting for him and I had to keep asking if cars really have all of these features he was being asked to say yea or nay to. It had been well over 20 years since I had owned a car and half of the features sounded indulgent and verging on sci-fi. He never got his car back let alone the books. But we did spend that Friday evening washing down a hefty steak with a fine Czech brew or two.
 
While still in Brno Patrick started a project that he pursued to the end of his working life. It is the Pattern Dictionary of English Verbs (PDEV), publicly available as an online database. He and his team studied concordances of verbs, tagging their grammatical and lexical features. They used Sketch Engine of course, since it was born and thrives to this day in the faculty where we were working. Sketch Engine achieved an international reach when the philosopher-linguist, Adam Kilgarriff, bought into it through a university–enterprise agreement. Adam died of cancer at the age of 55. In fact, the last time I saw Patrick was at Adam's funeral in Brighton.
 
Here is the entry for adapt in PDEV.

Every meaning/use of a verb has a unique pattern, which is why we know which meaning of a verb is meant when we read or hear it. And we use this information when we write and speak. Native speakers do this subconsciously while non-native speakers learn this, although to the best of my knowledge, there are no vocabulary teaching resources that employ this user-friendly description of meaning. I'm working on it! Watch this space. While an entry does not employ terminology such as valency, complementation or transitivity, it does use semantic types which are indicated in square brackets. The PDEV entry for answer has 14 entries, two of which are tagged phrasal: answer back and answer for and two are tagged idiom: have a lot to answer for and answer call of nature.
 
I participated in the PDEV corpus work for a short time. I was convinced that the searches could be partially automated as I had developed database scripts for automating Sketch Engine CQL searches for verbs in their known grammar patterns as part of my MA dissertation research. But Patrick preferred to work from raw data without skewing observations towards predetermined patterns. He also rejected intuition. There were times when I pointed out that the data did not show something about a verb that should be part of its description.
 
While his interest was in verbs, mine lay in nouns as the primary carriers of meaning in message clauses. I posited applying the PDEV approach to nouns, but Patrick had a completely different methodology for this part of speech. The cognitive profile, as he called it, consists of a set of short, objective sentences each sentence revolving around a collocation of the noun. For example, his spider profile includes these sentences:

• Some species of spiders hunt prey.
• Spiders lurk in the centres of their webs.
• Spiders have eight legs.
• Many people have a dread of or are frightened of spiders.

 
I have adapted this for teaching purposes, preferring the more student-friendly term, word profile. In pedagogical circles, a cognitive profile is more likely to pertain to a student than a word. I'll elaborate in another post.
 
I took him a couple of times to visit the old folks in Mikulov, a beautiful Moravian town on the Austrian border. The old folks were my dear friends, a Czech man and his South African wife, who had lived in my town, Sydney, for 15 years before moving to Czechia after the fall of the wall. We used to chat at the bar in their house, drink carafes of Moravian wine, play Noel and Cole on June's Steinway and stumble home the following day.
 
Patrick did invite me to stay with him for a few days in Bristol during which time he was frantically busy, but we did manage to talk about pattern descriptions of nouns, about his loneliness, his depressive moods, his ex-wife and his beloved daughter.
 
I can't imagine where my thinking about language would be had I not spent this time with Patrick. They were pivotal years for me, and it is a great honour to have been in his presence. You are very well-remembered, dear friend.