Download PDF by Striegnitz K., et al.: Algorithms for computational linguistics

By Striegnitz K., et al.

The identify Computational Linguistics already means that this displine contains comparable gadgets of study: traditional language (NL) is studied and operational tools are built. either fields are investigated of their personal correct and divide into a variety of issues. This path introduces a number of NL phenomena including acceptable implementations within the programming language Prolog. the subjects handled are between others Morphology, Finite country options, Syntax, Context loose Grammars, Parsing, and Semantics building.

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The predicate consists of two clauses. The second one is the one that succeeds in our example, so let’s look at it first. After unifying the two arguments A and S respectively with the the instruction cp(a1,b1) and the state name 1 in the head, the call to assert/1 in the first line of the body adds an entry state(cp(a1,b1),1) to the database. This marks state 1 as processed in copying cp(a1,b1). Next, it is checked if S is a final state. This is done using check_final/2. We will look at the code later.

5 we looked at one direction of the equivalence between regular expressions and FSAs. We showed that every language that can be characterized by a regular expression is also accepted by some FSA. Now let’s look at the other direction and prove that for every FSA there is a regular expression that characterizes the same language. 6. Exercises be a deterministic FSA, and L be the language accepted by it. We are going to show that there is also a regular expression for L. Before we begin, let’s define the following notion: R kij are those strings that M reads when it goes from i to j without passing through a state numbered higher than k (by passing through, we mean entering and leaving again).

Using the loop from 2 to 3 and back. On our way through this loop we read ha (the second occurence, to be precise). And we can go through this loop any number of times. , hahahaha! etc. The above considerations lead to the following lemma, known as the ‘Pumping Lemma’, because it says that we can ‘pump’ up words in regular languages under certain conditions. (By wi we mean the result of repeating w i-times; w i ✞ ε. ): 42 Chapter 3. Regular Languages Let L be a regular set. There is a constant n such that if w is any word that is in L and is of length greater n, then we can split w in parts w 1 vw2 with ✠ w1 v ✠✒✱ n and ✠ v ✠✜✟ 1, and w1 vi w2 is in L, too for all i ✟ 0.

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Algorithms for computational linguistics by Striegnitz K., et al.

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