All posts filed under: Wine Words

Brexit in a glass

One week on… let’s look at some wine vocabulary that also appears in the Brexit news. Can wine inform our understanding of Brexit related attitudes? (If you’re new to these posts, I’d recommend looking here first to understand what these wine-note visualizations are about.) An Isomap reduction of Brexit related wine-tasting vocab shows power orbited by seductiveness, with ominous words like pit, cut, hole and loose nearby. The picture suggests that power can move into expensive or complex but not both. As you move upwards from power, you get sickly, disjointed, sour. On the right it may get exciting and energetic. The further you leave the complexity behind, the more overwhelming it gets, by Gove! Through the PCA lens (our preferred view in previous posts on tasting note visualization), power lies closer to austerity. In both pictures, there’s some bitterness over access. Whatever the reasons May be, there also seems to be a seductive connection between  intrusive  and  borderline. The consolations of coffee and alcohol are linked to rising unpleasantness. So there you have it: wine-tasting visualizations can double as guides through essential Brexit concepts and the links between them. A glass of wine may improve political acuity. We form natural …

Fruity

And the orange squeezed into the water seemed to yield to me, as I drank, the secret life of its ripening growth, its beneficent action upon certain states of that human body which belongs to so different a kingdom, its powerlessness to make that body live, but on the other hand the process of irrigation by which it was able to benefit it, a hundred mysteries concealed by the fruit from my senses, but not from my intellect. Marcel Proust, Sodome et Gomorrhe, trans. Moncrieff.   Before there is wine, there is fruit* and juice. Before we learn to appreciate wine and cider, we instinctively enjoy the taste of grapes and apple juice, just like we enjoy beer before we move on to whiskey.   In this picture of clustered fruit descriptors, we see three interesting clusters. On the bottom left we have the citrus fruit moving up into riper fruit. Some of the less frequent descriptors stand out on the side, like mirabelle, lichee and banana and fig. Then we have a berry cluster which moves up …

Tasting Algos, Spring III: Funky

Going through some of Philip White’s older posts, I came across: “What the funk do they mean?“. What’s a funky wine? Here are some of the associations he comes up with: Tobacco Stinky Naughty Passionate Soulful Pleasing Attractive Swindler Cheater Thief Whereas the text analysis says Cheesy Brett Sweat Stewed Tired Soap Curious Oxidised Muddy Not sure if this answers White’s question or which of the lists is preferable. At any rate, with imagination, they’re not all that far apart.    MK@WineQuant    

Chocolate and Fennel?

This is Models vs. Reality, Part 2. I looked at what our tool has to say about chocolate as a wine descriptor and I was a bit surprised by the result. Top 10 chocolate related descriptors in critic wine notes cocoa coffee pepper tar mocha licorice truffle fennel vanilla espresso I would never have made an association between chocolate and fennel. It turns out that only a few writers make this connection. You can verify this yourself. For example on jancisrobinson.com you find that there are only six tasting notes including fennel and chocolate. Out of these, five are written by Tamlyn Currin and one is by Richard Hemming. None of these notes are in our dataset, so it’s a good test to look at them in a bit more detail. Chocolate and fennel, really? Richard Hemming’s description of an Alvaro Palacios Priorat (65% Carignan) features “leather and fennel aromas” with “chocolate-covered cherry”. Tamlyn Currin describes a “delicious mouthful of sweet red pepper and dried herbs, liquorice and chocolate” followed by a long finish with “a thrill of fennel and aniseed” in a …

Models vs. Reality, Part 1

Wine appreciation requires language. But the way you use language depends on what you consider to be a “good tasting note.” What is good? What’s the norm? …writing is a learned activity, no different in that regard from hitting a golf ball or playing the piano. Yes, some people naturally do it better than others. But apart from a few atypical autodidacts (who exist in all disciplines), there’s no practical way to learn to write, hit a golf ball, or play the piano without guidance on many points, large and small. And everyone, even the autodidact, requires considerable effort and practice in learning the norms. The norms are important even to those who ultimately break them to good effect. Bryan A. Garner, Garner’s Modern American Usage (2009, p. 104) Famous critics and formal tasting systems provide models/norms/reference points. But how good are those norms? What does “green apple, citrus peel, medium+ acidity” mean, exactly? Models are useful, but only if we don’t lose touch with what is actually going on. So let’s calibrate our models to reality. …

Tasting Algos, Spring I.

You shall know a word by the company it keeps (Firth, J. R.) It’s reasonable to believe that wine words which occur in similar contexts have related meanings for the tasters who wrote them down. Join us on our machine assisted journey to explore the unplumbed depths of wine writing with natural language processing (NLP) techniques. As machine learning meets human taste, let’s strive to make the symbiosis fruitful: with NLP algorithms and computing power at our fingertips, here’s an opportunity to discover more about how we record sensory impressions with words. We’ve trained neural network models on a large corpus of wine notes to recognize words by the company they keep. The results are fascinating. It’s spring-time, so let’s start by investigating a couple of fresh, uplifting, seasonal descriptors that come to mind naturally. Each word comes with its top 10 contextual associates picked out by our machine assistant.  The score (cosine similarity) indicates how close the association is. Blossoms ‘peaches’, 0.64 ‘wax’, 0.64 ‘poached’, 0.62, ‘bursts’, 0.61 ‘hazelnuts’, 0.61 ‘apples’, 0.61 ‘buttered’, 0.60 ‘apricots’, 0.60 ‘candle’, …

Wine Words to Data

It’s not always easy to find the wine market data you need. And even when you know where the data you need is, it can be expensive to get it. (If you’re ever stuck getting the data you require, let us know and we’ll help!) The secondary market for wine is fascinating! But there’s more to a wine than its price. Let’s take a step closer to the source. How about the fine line between sublime tasting note and, how can we put it delicately…  bullshit? That’s an area worth investigating. Luckily there is more free wine tasting data than you could usefully process. To tackle the wine word challenge, we’ve strengthened the WineQuant team with a NLP specialist. (All will be revealed in due course.) In the mean time, here are some introductory thoughts. Wise Words?* Conveying sensory impressions in words is difficult. Émile Peynaud (1912-2004), a Bordelais legend among oenologists and wine-writers remarked that “we tasters feel to some extent betrayed by language.” How can writers convey information about colour, sound and taste …