WEBVTT

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All right, everyone.

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So let's dive into how to create those rule-based matching packed on inside the Biton code.

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And for that, I have already created a detailed notebook, so you can see.

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So let us start working on it.

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First, let's just look at our model.

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So nothing special, nothing different here.

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And to create any kinds of pattern in this rule is matching stuff you hope with first creator Metcher

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object.

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And this measured object is a part of spacy dark matter.

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And from that, you can just import this matches.

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And from that measure, you can create one match, an object.

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Now, interesting thing will light while creating the pattern that we think was created while defining

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different kinds of patterns here.

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You can see this is called laser one pattern.

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All right.

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So let me run all of them.

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And let me create the matter object.

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All right, so let's say we want to grab.

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The lower case was a..

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Hello, and Voight has a pattern or a token together.

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So there will be a one pattern I have defined like a hollow space.

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Well, it will find out.

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Or suppose you feel right.

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Hello.

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Well, also, it will find out or if you let's say do hello and.

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One.

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So Lenore Keyes was an off hand, low token and lower case was an avoid.

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Easy to piece together.

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The pattern underscored.

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One will have to find out.

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Now there is on one more pattern.

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Define.

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So there will be a lowercase was enough.

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Hello.

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And then I just kept his underscored punctuation.

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Mark will be to.

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So any punctuation mark exist between this lowercase was one of two pattern respectively.

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Hello.

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And what I really want to find out with this pattern number two.

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All right.

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So let me define this mode of this pattern.

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And this pattern got defined as a list.

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An individual element of this list will be a dictionary.

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Now, as we have seen, along with I mean, apart from this Lowitt, there are a number of attributes

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that are possible.

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Like you can see from your land, whether you want to search for something is is Hafize contrition moggy

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space like you are, in fact, hoes, entity type.

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You'll see.

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All right.

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So I don't want to quite define next is whatever the matcher object V created V how to act both of these

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packett.

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So that will be a pattern in this code and pattern.

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Underscore the.

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Let me let me know how our pattern got defined.

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We have added this pattern to the matched object.

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Next is our documents should be ready.

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So I've created one document where there is one HelloWallet like this.

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And then you can see the one Healthway will be like this with punctuation Mark.

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So let me add any.

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And next steps we need to find those matches.

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So we dealt for Metcher object.

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We are going to apply this document, object to the match.

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And it will find out all those matches.

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Now, this matches will just return as the document index or kocon index number.

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That will be two and a fold.

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So if you see here.

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Two and a four, so that will be a two.

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And this will be a plea.

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So that means one to two for the upper bound is always excluded.

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That's why it has returned like from two to four.

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They are able to find one match phone and the same way like 19 to 22.

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So this is pointing to 19 then.

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So Helo's pointed by 19 men under Goken will be hyphen, which is pointed by twenty twenty one is pointing

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the way.

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And obviously 22 will be excluded because it's an one.

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Now, if you get somewhat more detailed description, you can just be true with this.

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Fine, the score matches object.

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So you can see and you will get a plea to place like a match already start.

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So first case, we are just getting the string representation of this match.

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That will be nothing but a string and a score.

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Right.

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And wherever the match found, the exact ping we are trying to display along with the starting next

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and end index.

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So if you executed.

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You can see who before hello.

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In here it is a 19 to 22.

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Hello.

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Hi, fun boy.

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Let's say if you just try to act on one more Halloween, let's say in between.

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Hello.

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And let's say.

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Hold capital.

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All right.

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Let me define it.

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Let's find the matches.

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And let's see whether it is a to identify.

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Yes, it has.

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It will be identified.

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That means every single pattern name like this, it has its own meaning.

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Take Venezuela.

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The lowercase words of hello will found.

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The match will be found.

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All right.

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So that is the one case.

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Let's see one more.

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So here we are defined like hallowing one just like earlier.

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But one more starting the how, Heidi.

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Like a puppy.

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So this is going to allow the pattern to match Gedo or more this type of punctuation mark.

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So suppose each any place, if that is.

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No.

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Nothing like some punctuation mark Xs Nanosolar.

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It is a bug to identify.

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So let me execute it.

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And let's find a match.

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And you can see it from three to five.

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So this is zero.

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One, two, three.

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So three, two, five, one match phone.

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Five six nine zero.

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One, two, three, four, five, six.

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Yes, six, seven and eight.

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And then again, this is nine, ten, eleven.

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Also quite far.

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So whether any punctuation mark in between exists or not, that doesn't matter.

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All right.

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So that is the story behind this rule based matching.

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You can go to the documentation and you will be able to see the detailed documentation regarding to

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all those token attributes has been written.

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What is the meaning of each individual like the law?

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We have used it.

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And when we tried it earlier, this entity type also we tried to digitize.

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So.

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So something you are searching for is lowered also.

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So you can refer to this particular documentation.

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And this is about the rule based matching.

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Next, we will see a place mismatching.

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So see you in the next video.
