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To support very large scale neural networks in limited amount of memory, one may want to use floating point numbers with very few bits. Here we consider substantially simplified operations on such numbers, Float8. A value Float8(mant,exp) represents the non-negative integer mant * 2^exp. We call mant a mantissa (which ... | A 2-bit float with 1-bit exponent and 1-bit mantissa would only have 0, 1, Inf, NaN values. If the mantissa is allowed to be 0-bit, a 1-bit float format would have a 1-bit exponent, and the only two values would be 0 and Inf. The exponent must be at least 1 bit or else it no longer makes sense as a float (it would just... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
To support very large scale neural networks in limited amount of memory, one may want to use floating point numbers with very few bits. Here we consider substantially simplified operations on such numbers, Float8. A value Float8(mant,exp) represents the non-negative integer mant * 2^exp. We call mant a mantissa (which ... | Floating-point numbers are typically packed into a computer datum as the sign bit, the exponent field, and the significand or mantissa, from left to right. For the IEEE 754 binary formats (basic and extended) which have extant hardware implementations, they are apportioned as follows: While the exponent can be positive... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Once paging is enabled, load instruction / CR3 register / Page Table entry uses Virtual or Physical address? | In protected mode with paging enabled (bit 31, PG, of control register CR0 is set), but without PAE, x86 processors use a two-level page translation scheme. Control register CR3 holds the page-aligned physical address of a single 4 KB long page directory. This is divided into 1024 four-byte page directory entries that ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Once paging is enabled, load instruction / CR3 register / Page Table entry uses Virtual or Physical address? | Used when virtual addressing is enabled, hence when the PG bit is set in CR0. CR3 enables the processor to translate linear addresses into physical addresses by locating the page directory and page tables for the current task. Typically, the upper 20 bits of CR3 become the page directory base register (PDBR), which sto... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the execution of an application are possible on a single-core machine? | A single-core processor is a microprocessor with a single core on its die. It performs the fetch-decode-execute cycle once per clock-cycle, as it only runs on one thread. A computer using a single core CPU is generally slower than a multi-core system. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the execution of an application are possible on a single-core machine? | A single kernel execution can run on all or many of the PEs in parallel. How a compute device is subdivided into compute units and PEs is up to the vendor; a compute unit can be thought of as a "core", but the notion of core is hard to define across all the types of devices supported by OpenCL (or even within the categ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the following lock acquisition orders (locks are acquired from left to right), for thread 1 (T1) and thread 2 (T2), will result in a deadlock ? Assume that A, B, C, D are lock instances. | Thus, the programmer must think of all possible combinations of one thread giving up a lock and another thread getting it next, and make sure their code only allows valid combinations. Note that the only effect is that A-post-gain-lock statements come before B-post-gain-lock statements. No other effect happens, and no ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the following lock acquisition orders (locks are acquired from left to right), for thread 1 (T1) and thread 2 (T2), will result in a deadlock ? Assume that A, B, C, D are lock instances. | The notion of fairness in lock acquisition applies to the order in which threads acquire a lock successfully. If some type of fairness is implemented, it prevents a thread from being starved out of execution for a long time due to inability to acquire a lock in favor of other threads. With no fairness guarantees, a sit... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
There are N philosphers sitting around a circular table eating spaghetti and discussing philosphy. The problem is that each philosopher needs two forks to eat, and there are only $N$ forks, one between each pair of philosophers. We want to design an algorithm that the philosophers can use, that ensures that no one star... | Each philosopher can only alternately think and eat. Moreover, a philosopher can only eat their spaghetti when they have both a left and right fork. Thus two forks will only be available when their two nearest neighbors are thinking, not eating. After an individual philosopher finishes eating, they will put down both f... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
There are N philosphers sitting around a circular table eating spaghetti and discussing philosphy. The problem is that each philosopher needs two forks to eat, and there are only $N$ forks, one between each pair of philosophers. We want to design an algorithm that the philosophers can use, that ensures that no one star... | A solution presented by William Stallings is to allow a maximum of n-1 philosophers to sit down at any time. The last philosopher would have to wait (for example, using a semaphore) for someone to finish dining before they "sit down" and request access to any fork. This guarantees at least one philosopher may always ac... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In an x86 multiprocessor system with JOS, select all the correct options. Assume every Env has a single thread. | OS-9's real-time kernel allows multiple independent applications to execute simultaneously through task switching and inter-process communication facilities. All OS-9 programs run as processes containing at least one lightweight process (thread) but may contain an effectively unlimited number of threads. Within a proce... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In an x86 multiprocessor system with JOS, select all the correct options. Assume every Env has a single thread. | Used to modify/check the number of threads, detect if the execution context is in a parallel region, how many processors in current system, set/unset locks, timing functions, etc | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Freshly graduated from EPFL, you have been hired as contractors for a successful and rapidly growing bank. The bank has been experiencing problems with their money management system recently, which is written in Scala, and so they hired the best and brightest young engineer they could find: you! The system had been wor... | One of lock-based programming's biggest problems is that "locks don't compose": it is hard to combine small, correct lock-based modules into equally correct larger programs without modifying the modules or at least knowing about their internals. Simon Peyton Jones (an advocate of software transactional memory) gives th... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Freshly graduated from EPFL, you have been hired as contractors for a successful and rapidly growing bank. The bank has been experiencing problems with their money management system recently, which is written in Scala, and so they hired the best and brightest young engineer they could find: you! The system had been wor... | Consider a banking application as an example, and a transaction in it—the transfer function, which takes money from one account, and puts it into another account. In the IO monad, this might look like: This causes problems in concurrent situations where multiple transfers might be taking place on the same account at th... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In this week's lecture, you have been introduced to the aggregate method of ParSeq[A] (and other parallel data structures). It has the following signature: def aggregate[B](z: B)(f: (B, A) => B, g: (B, B) => B): B Discuss, as a group, what aggregate does and what its arguments represent. Discuss the implementations fr... | There are no readily available heuristics available that are accurate with large databases. This method has only been used by Ringe's group.In these two methods there are often several trees found with the same score so the usual practice is to find a consensus tree via an algorithm. A majority consensus has bipartitio... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In this week's lecture, you have been introduced to the aggregate method of ParSeq[A] (and other parallel data structures). It has the following signature: def aggregate[B](z: B)(f: (B, A) => B, g: (B, B) => B): B Discuss, as a group, what aggregate does and what its arguments represent. Discuss the implementations fr... | It has been claimed that for complex queries OLAP cubes can produce an answer in around 0.1% of the time required for the same query on OLTP relational data. The most important mechanism in OLAP which allows it to achieve such performance is the use of aggregations. Aggregations are built from the fact table by changin... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following contains function defined on Iterable (in particular, it accepts both Vector and List). def contains[A](l: Iterable[A], elem: A): Boolean = val n = l.size if n <= 5 then for i <- l do if i == elem then return true false else val (p0, p1) = parallel( contains... | This can happen for at most 2K(x,y)-l = 2k different strings. These strings can be enumerated given k,l and hence x can be specified by its index in this enumeration. The corresponding program for x has size k + O(1). Theorem proved. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following contains function defined on Iterable (in particular, it accepts both Vector and List). def contains[A](l: Iterable[A], elem: A): Boolean = val n = l.size if n <= 5 then for i <- l do if i == elem then return true false else val (p0, p1) = parallel( contains... | An exact cover problem is defined by the binary relation "contains" between subsets in S and elements in X. There are different equivalent ways to represent this relation. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In JOS, suppose a value is passed between two Envs. What is the minimum number of executed system calls? | Hence 0 ≤ i ≤ u, and 0 ≤ j ≤ u. Let A be the number of ways of assigning the j output calls to the m middle stage switches. Let B be the number of these assignments which result in blocking. This is the number of cases in which the remaining m−j middle stage switches coincide with m−j of the i input calls, which is the... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In JOS, suppose a value is passed between two Envs. What is the minimum number of executed system calls? | As an example of one of the more elaborate IPL-handling systems ever deployed, the VAX computer and associated VMS operating system supports 32 priority levels, from 0 to 31. Priorities 16 and above are for requests from external hardware, while values below 16 are available for software interrupts (used internally by ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
What strace tool does? | strace is a diagnostic, debugging and instructional userspace utility for Linux. It is used to monitor and tamper with interactions between processes and the Linux kernel, which include system calls, signal deliveries, and changes of process state. The operation of strace is made possible by the kernel feature known as... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
What strace tool does? | The most common use is to start a program using strace, which prints a list of system calls made by the program. This is useful if the program continually crashes, or does not behave as expected; for example using strace may reveal that the program is attempting to access a file which does not exist or cannot be read. ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following grammar:
S -> NP VP
NP -> Det N
VP -> VBe Adj
NP -> NP PP
VP -> V
N -> Adj N
VP -> VP PP
Adj -> Adj PP
V -> VBe
Adj -> Ving
PP -> Prep NP
and the following lexicon:
at:Prep is:VBe old:Adj
black:Adj looking:Ving the:Det
cat:N mouse:N under:Prep
former:Adj nice:Adj with:Prep
The above grammar ... | At the time, PPs were considered to immediately dominate P and NP, and APs and AdvPs were seen as dominating or being dominated by NPs. Ross' constraints apply to English, but they are not universally applicable to all languages. The fact that pied-piping varies so much across languages is a major challenge facing theo... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following grammar:
S -> NP VP
NP -> Det N
VP -> VBe Adj
NP -> NP PP
VP -> V
N -> Adj N
VP -> VP PP
Adj -> Adj PP
V -> VBe
Adj -> Ving
PP -> Prep NP
and the following lexicon:
at:Prep is:VBe old:Adj
black:Adj looking:Ving the:Det
cat:N mouse:N under:Prep
former:Adj nice:Adj with:Prep
The above grammar ... | This rule requires the tense-marked verb of a main clause to occur in the second position of the sentence, even if that means it comes before the subject (e.g. there is an adverb at the beginning of the sentence). These speakers' ability to form sentences with V2 word order was compared against L2 learners who often ov... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The goal of this question is to illustrate how to use transducers to implement a simplified version of the conjugation of English verbs. We will restrict to the conjugated forms corresponding to the indicative mode and the present tense.
The idea is to build a transducer corresponding to the composition of three transd... | The following table presents a comparison of conjugations of the thematic present indicative of the verbal root *bʰer- of the English verb to bear and its reflexes in various early attested IE languages and their modern descendants or relatives, showing that all languages had in the early stage an inflectional verb sys... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The goal of this question is to illustrate how to use transducers to implement a simplified version of the conjugation of English verbs. We will restrict to the conjugated forms corresponding to the indicative mode and the present tense.
The idea is to build a transducer corresponding to the composition of three transd... | In general, the following transformations take place: ô → o, o → u, æ → e, e → i, and a → e (the latter only in the perfect tenses), where the verbal noun features the first vowel but certain conjugations use the second. In addition, the verbs দেওয়া (dêoa , to give) and নেওয়া (nêoa, to take) switch between e, i, a, a... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
According to your knowledge of English, split the following sentence into words and punctuation:
M. O'Connel payed $ 12,000 (V.T.A. not included) with his credit card.
Which of these words won't usually be in a standard lexicon? Justify your answer. Assuming separators are: whitespace, quote ('), full-stop/period (.),... | Typically, lexical tokenization occurs at the word level. However, it is sometimes difficult to define what is meant by a "word". Often a tokenizer relies on simple heuristics, for example: Punctuation and whitespace may or may not be included in the resulting list of tokens. All contiguous strings of alphabetic charac... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
According to your knowledge of English, split the following sentence into words and punctuation:
M. O'Connel payed $ 12,000 (V.T.A. not included) with his credit card.
Which of these words won't usually be in a standard lexicon? Justify your answer. Assuming separators are: whitespace, quote ('), full-stop/period (.),... | Lexical analysis mainly segments the input stream of characters into tokens, simply grouping the characters into pieces and categorizing them. However, the lexing may be significantly more complex; most simply, lexers may omit tokens or insert added tokens. Omitting tokens, notably whitespace and comments, is very comm... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | In formal language theory, a context-free grammar, G, is said to be in Chomsky normal form (first described by Noam Chomsky) if all of its production rules are of the form: A → BC, or A → a, or S → ε,where A, B, and C are nonterminal symbols, the letter a is a terminal symbol (a symbol that represents a constant value)... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | The dynamic programming algorithm requires the context-free grammar to be rendered into Chomsky normal form (CNF), because it tests for possibilities to split the current sequence into two smaller sequences. Any context-free grammar that does not generate the empty string can be represented in CNF using only production... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Explain the difference between inflectional and derivational morphology. Illustrate your explanation with concrete examples in English or French. | Derivation can be contrasted with inflection, in that derivation produces a new word (a distinct lexeme), whereas inflection produces grammatical variants (or forms) of the same word. Generally speaking, inflection applies in more or less regular patterns to all members of a part of speech (for example, nearly every En... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Explain the difference between inflectional and derivational morphology. Illustrate your explanation with concrete examples in English or French. | Bound morphemes can be further classified as derivational or inflectional morphemes. The main difference between them is their function in relation to words. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the answer that correctly describes the differences between formal and natural languages. | A formalization is correct if its explicit logical features fit the implicit logical features of the original sentence. The logical form of ordinary language sentences is often not obvious since there are many differences between natural languages and the formal languages used by logicians. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the answer that correctly describes the differences between formal and natural languages. | A formalization is correct if its explicit logical features fit the implicit logical features of the original sentence. The logical form of ordinary language sentences is often not obvious since there are many differences between natural languages and the formal languages used by logicians. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. You have been given the results of three different systems that have been evaluated on the same panel of 157... | E-mail spam problem is a common classification problem, in this problem, 57 features are used to classify spam e-mail and non-spam e-mail. Applying IJ-U variance formula to evaluate the accuracy of models with m=15,19 and 57. The results shows in paper( Confidence Intervals for Random Forests: The jackknife and the Inf... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. You have been given the results of three different systems that have been evaluated on the same panel of 157... | As data is entered, the system includes new rules; if we consider that this data can generalize the training data information, then we have to evaluate the system development and measure the system's ability to correctly predict the categories of new information. This step is simplified by separating the training data ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In an automated email router of a company, we want to make the distinction between three kind of
emails: technical (about computers), financial, and the rest ('irrelevant'). For this we plan to use a
Naive Bayes approach.
What is the main assumption made by Naive Bayes classifiers? Why is it 'Naive'?
We will consider ... | Naive Bayes classifiers are a popular statistical technique of e-mail filtering. They typically use bag-of-words features to identify email spam, an approach commonly used in text classification. Naive Bayes classifiers work by correlating the use of tokens (typically words, or sometimes other things), with spam and no... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In an automated email router of a company, we want to make the distinction between three kind of
emails: technical (about computers), financial, and the rest ('irrelevant'). For this we plan to use a
Naive Bayes approach.
What is the main assumption made by Naive Bayes classifiers? Why is it 'Naive'?
We will consider ... | In statistics, naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features (see Bayes classifier). They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can a... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the following are parameters involved in the choice made by an order-1 HMM model for PoS tagging knowing that its output isthis/Pron is/V a/Det good/Adj question/Nand that neither "is" nor "question" can be adjectives, and that "question" can also not be a determiner.(Penalty for wrong ticks.) | Those tag questions which expect an affirmative answer may employ the particle xom in second position within the sentence. Comparing statement, yes/no question, and tag question expecting an affirmative answer: Dghes k'argi amindia, 'The weather is good today' Dghes k'argi amindia?, 'is the weather good today?' Dghes x... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Which of the following are parameters involved in the choice made by an order-1 HMM model for PoS tagging knowing that its output isthis/Pron is/V a/Det good/Adj question/Nand that neither "is" nor "question" can be adjectives, and that "question" can also not be a determiner.(Penalty for wrong ticks.) | The same method can, of course, be used to benefit from knowledge about the following words. More advanced ("higher-order") HMMs learn the probabilities not only of pairs but triples or even larger sequences. So, for example, if you've just seen a noun followed by a verb, the next item may be very likely a preposition,... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
For each of the sub-questions of this question (next page), tick/check the corresponding box if the presented sentence is correct
at the corresponding level (for a human). There will be a penalty for wrong boxes ticked/checked.Some sentences is hard understand to. | The respondent is required to click on the box next to the answer that corresponds to the desired choice. A checkmark will appear in the box once an answer is chosen. More than one answer can be selected. If there are many options, a simple matrix is recommended. When using check boxes, if more than one answer can be c... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
For each of the sub-questions of this question (next page), tick/check the corresponding box if the presented sentence is correct
at the corresponding level (for a human). There will be a penalty for wrong boxes ticked/checked.Some sentences is hard understand to. | It occurs often in English in tag questions, as in "It's too late, isn't it?" If the tag question ("isn't it") is spoken with rising intonation, an answer is expected (the speaker is expressing doubt), while if it is spoken with falling intonation, no answer is necessarily expected and no doubt is being expressed. Sent... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. You have been given the results of three different systems that have been evaluated on the same panel of 157... | E-mail spam problem is a common classification problem, in this problem, 57 features are used to classify spam e-mail and non-spam e-mail. Applying IJ-U variance formula to evaluate the accuracy of models with m=15,19 and 57. The results shows in paper( Confidence Intervals for Random Forests: The jackknife and the Inf... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. You have been given the results of three different systems that have been evaluated on the same panel of 157... | Once trained, the learned patterns would be applied to the test set of e-mails on which it had not been trained. The accuracy of the patterns can then be measured from how many e-mails they correctly classify. Several statistical methods may be used to evaluate the algorithm, such as ROC curves. If the learned patterns... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the morpho-syntactic categories that do not carry much semantic content and are thus usually filtered-out from indexing. | See demonstrative. Note that some categories are regular and some are not. They may be regular or irregular also depending on languages. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the morpho-syntactic categories that do not carry much semantic content and are thus usually filtered-out from indexing. | Direct systems depend on the notion of filtered categories. For example, the category N, whose objects are natural numbers, and with exactly one morphism from n to m whenever n ≤ m {\displaystyle n\leq m} , is a filtered category. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following CFG
\(\text{S} \rightarrow \text{NP VP PNP}\)
\(\text{NP} \rightarrow \text{Det N}\)
\(\text{NP} \rightarrow \text{Det Adj N}\)
\(\text{VP} \rightarrow \text{V}\)
\(\text{VP} \rightarrow \text{Aux Ving}\)
\(\text{VP} \rightarrow \text{VP NP}\)
\(\text{VP} \rightarrow \text{VP PNP}\)
\(\text{PNP}... | This is an example grammar: S ⟶ NP VP VP ⟶ VP PP VP ⟶ V NP VP ⟶ eats PP ⟶ P NP NP ⟶ Det N NP ⟶ she V ⟶ eats P ⟶ with N ⟶ fish N ⟶ fork Det ⟶ a {\displaystyle {\begin{aligned}{\ce {S}}&\ {\ce {->NP\ VP}}\\{\ce {VP}}&\ {\ce {->VP\ PP}}\\{\ce {VP}}&\ {\ce {->V\ NP}}\\{\ce {VP}}&\ {\ce {->eats}}\\{\ce {PP}}&\ {\ce {->P\ NP... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following CFG
\(\text{S} \rightarrow \text{NP VP PNP}\)
\(\text{NP} \rightarrow \text{Det N}\)
\(\text{NP} \rightarrow \text{Det Adj N}\)
\(\text{VP} \rightarrow \text{V}\)
\(\text{VP} \rightarrow \text{Aux Ving}\)
\(\text{VP} \rightarrow \text{VP NP}\)
\(\text{VP} \rightarrow \text{VP PNP}\)
\(\text{PNP}... | Input: Received word y = ( y 0 , … , y 2 n − 1 ) {\displaystyle y=(y_{0},\dots ,y_{2^{n}-1})} For each i ∈ { 1 , … , n } {\displaystyle i\in \{1,\dots ,n\}}: Pick j ∈ { 0 , … , 2 n − 1 } {\displaystyle j\in \{0,\dots ,2^{n}-1\}} uniformly at random. Pick k ∈ { 0 , … , 2 n − 1 } {\displaystyle k\in \{0,\dots ,2^{n}-1\}}... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Give well chosen examples of applications that can be evaluated with the single metric derived from Precision/Recall and illustrate:
• a situation where more weight should be given to Precision;
• a situation where more weight should be given to Recall. | This raises the need for evaluation metrics which can quantify performance on large, ranked lists. LBD works have used metrics popular in Information Retrieval which include Precision, Recall, Area Under the Curve (AUC), Precision at k, Mean Average Precision (MAP) and others.The approach of Proposing new discoveries o... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Give well chosen examples of applications that can be evaluated with the single metric derived from Precision/Recall and illustrate:
• a situation where more weight should be given to Precision;
• a situation where more weight should be given to Recall. | During the evaluation of WSD systems two main performance measures are used: Precision: the fraction of system assignments made that are correct Recall: the fraction of total word instances correctly assigned by a systemIf a system makes an assignment for every word, then precision and recall are the same, and can be c... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The company finally decides to implement a hybrid model consisting of a 4-gram character model combined (independently) with a 3-gram word model.How many parameters would such a hybrid model have in total?Provide the answer in the form 10^A + 10^B (for instance, write "10^7 + 10^9"). | This would give a model perplexity of 2190 per sentence. However, it is more common to normalize for sentence length. Thus, if the test sample's sentences comprised a total of 1,000 words, and could be coded using 7.95 bits per word, one could report a model perplexity of 27.95 = 247 per word. In other words, the model... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The company finally decides to implement a hybrid model consisting of a 4-gram character model combined (independently) with a 3-gram word model.How many parameters would such a hybrid model have in total?Provide the answer in the form 10^A + 10^B (for instance, write "10^7 + 10^9"). | One gets n 2 − n 2 + n − 1 = 1 2 n 2 + 1 2 n − 1. {\displaystyle {{n^{2}-n} \over 2}+n-1={1 \over 2}n^{2}+{1 \over 2}n-1.} For example, for an amino acid sequence (there are 20 "standard" amino acids that make up proteins), one would find there are 209 parameters. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Give some concrete examples of NLP applications that might benefit from the semantic vectorial representations. | This approach was also extended to multilingual domains, fine entity typing and other problems. Moreover, beyond relying solely on representations, the computational approach has been extended to depend on transfer from other tasks, such as textual entailment and question answering.The original paper also points out th... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Give some concrete examples of NLP applications that might benefit from the semantic vectorial representations. | Hans van Halteren, Jakub Zavrel, Walter Daelemans. 2001. Improving Accuracy in NLP Through Combination of Machine Learning Systems. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following lexicon \(L\):
boy : Adj, N
boys : N
blue : Adj, N
drink : N, V
drinks : N, V
Nice : Adj, N
When using an order-1 HMM model (using \(L\)) to tag the word sequence:"Nice boys drink blue drinks"does the tag of drink depend on the tag of nice?
| Sequence tagging is a class of problems prevalent in natural language processing, where input data are often sequences (e.g. sentences of text). The sequence tagging problem appears in several guises, e.g. part-of-speech tagging and named entity recognition. In POS tagging, for example, each word in a sequence must rec... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following lexicon \(L\):
boy : Adj, N
boys : N
blue : Adj, N
drink : N, V
drinks : N, V
Nice : Adj, N
When using an order-1 HMM model (using \(L\)) to tag the word sequence:"Nice boys drink blue drinks"does the tag of drink depend on the tag of nice?
| In the mid-1980s, researchers in Europe began to use hidden Markov models (HMMs) to disambiguate parts of speech, when working to tag the Lancaster-Oslo-Bergen Corpus of British English. HMMs involve counting cases (such as from the Brown Corpus) and making a table of the probabilities of certain sequences. For example... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Up to which linguistic processing level can each of the following sentences be considered as correct? The glass broke its leg, I no go rain, The cook put cherry stones in the cake, Cars flow beautifully; syntactic, pragmatic, syntactic, semantic, lexical | Several syntactic hypotheses can be considered at a time. The interactive model demonstrates an on-line interaction between the structural and lexical and phonetic levels of sentence processing. Each word, as it is heard in the context of normal discourse, is immediately entered into the processing system at all levels... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Up to which linguistic processing level can each of the following sentences be considered as correct? The glass broke its leg, I no go rain, The cook put cherry stones in the cake, Cars flow beautifully; syntactic, pragmatic, syntactic, semantic, lexical | Several syntactic hypotheses can be considered at a time. The interactive model demonstrates an on-line interaction between the structural and lexical and phonetic levels of sentence processing. Each word, as it is heard in the context of normal discourse, is immediately entered into the processing system at all levels... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Describe the main principles of the standard vector space model for semantics. | Models based on and extending the vector space model include: Generalized vector space model Latent semantic analysis Term Rocchio Classification Random indexing Search Engine Optimization | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Describe the main principles of the standard vector space model for semantics. | 1999. Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You are responsible for a project aiming at providing on-line recommendations to the customers of
a on-line book selling company.
The general idea behind this recommendation system is to cluster books according to both customers
and content similarities, so as to propose books similar to the books already bought by a g... | Recommender systems Recommender systems are designed to recommend new items based on a user's tastes. They sometimes use clustering algorithms to predict a user's preferences based on the preferences of other users in the user's cluster. Markov chain Monte Carlo methods Clustering is often utilized to locate and charac... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You are responsible for a project aiming at providing on-line recommendations to the customers of
a on-line book selling company.
The general idea behind this recommendation system is to cluster books according to both customers
and content similarities, so as to propose books similar to the books already bought by a g... | Recommender systems Recommender systems are designed to recommend new items based on a user's tastes. They sometimes use clustering algorithms to predict a user's preferences based on the preferences of other users in the user's cluster. Markov chain Monte Carlo methods Clustering is often utilized to locate and charac... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
If there are {t} PoS tags, what is the maximum number of (not necessarily free) parameters the probabilistic model needs to consider to determine the best possible PoS tag sequence given a word sequence of length {w}, subjected to the limited lexical conditioning and limited scope for syntactic dependencies (1 neighbor... | A statistical tagger looks for the most probable tag for an ambiguously tagged text σ σ … σ {\displaystyle \sigma \sigma \ldots \sigma }: γ ∗ … γ ∗ = arg m a x γ ∈ T ( σ ) p ( γ … γ σ … σ ) {\displaystyle \gamma ^{*}\ldots \gamma ^{*}=\operatorname {\arg \,max} _{\gamma \in T(\sigma )}p(\gamma \ldots \gamm... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
If there are {t} PoS tags, what is the maximum number of (not necessarily free) parameters the probabilistic model needs to consider to determine the best possible PoS tag sequence given a word sequence of length {w}, subjected to the limited lexical conditioning and limited scope for syntactic dependencies (1 neighbor... | This version of the halting problem is among the simplest, most-easily described undecidable decision problems: Given an arbitrary positive integer n and a list of n+1 arbitrary words P1,P2,...,Pn,Q on the alphabet {1,2,...,n}, does repeated application of the tag operation t: ijX → XPi eventually convert Q into a word... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the statements that are true.A penalty will be applied to any incorrect answers selected. | In computer languages it is expected that any truth-valued expression be permitted as the selection condition rather than restricting it to be a simple comparison. In SQL, selections are performed by using WHERE definitions in SELECT, UPDATE, and DELETE statements, but note that the selection condition can result in an... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select the statements that are true.A penalty will be applied to any incorrect answers selected. | Suppose a student is to write a multiple-choice test; for simplicity, assume the test is a list of statements which are either true or false. To prepare for the test, the student comes up with two games, or strategies: Game A: given a statement, answer "true". Game B: given a statement, answer "false".By sticking to Ga... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Your aim is to evaluate a movie review analysis system, the purpose of which is to determine whether a review is globally positive or negative.
For each movie review, such a system outputs one of the following classes: positive and negative.
To perform your evaluation, you collect a large set of reviews and have it an... | It is necessary for the critic to do so as some reviews are qualitative and do not grant a numeric score, making it impossible for the system to be automatic.The website keeps track of all the reviews counted for each film and calculates the percentage of positive reviews. Major recently released films can attract more... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Your aim is to evaluate a movie review analysis system, the purpose of which is to determine whether a review is globally positive or negative.
For each movie review, such a system outputs one of the following classes: positive and negative.
To perform your evaluation, you collect a large set of reviews and have it an... | Websites such as Rotten Tomatoes and Metacritic seek to improve the usefulness of film reviews by compiling them and assigning a score to each in order to gauge the general reception a film receives. Another aggregator is the Movie Review Query Engine, which is a large data storage on the internet that stores interview... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been publishing a daily column for the Gazette over the last few years and have recently reached a milestone --- your 1000th column! Realizing you'd like to go skiing more often, you decide it might be easier to automate your job by training a story generation system on the columns you've already written. Then... | An individual or small business might have this publishing process: Brainstorm content ideas to publish, where to publish, and when to publish Write each piece of content based on the publication schedule Edit each piece of content Publish each piece of contentA larger group might have this publishing process: Brainsto... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been publishing a daily column for the Gazette over the last few years and have recently reached a milestone --- your 1000th column! Realizing you'd like to go skiing more often, you decide it might be easier to automate your job by training a story generation system on the columns you've already written. Then... | The subject matter of the (now fortnightly, earlier weekly) magazine ranges from articles about techniques and tools to profiles of full-size prototypes of modelling subjects. The main content is, however, 'constructional articles' describing projects at various levels of detail. Such articles range from single pages t... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
For each of the following pairs, what kind of morphology is involved? cat+N => cats, break+V => breakable , freeze+V => frozen , translate+V => translation, modify+V => modifies ; inflectional, inflectional, derivational, inflectional, derivational | For example, in the word "cat", the component "cat" makes sense as does "at", but "at" does not mean the same thing as "cat". In this example, "ca" does not mean anything. Morphology is the study of words and how they are formed. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
For each of the following pairs, what kind of morphology is involved? cat+N => cats, break+V => breakable , freeze+V => frozen , translate+V => translation, modify+V => modifies ; inflectional, inflectional, derivational, inflectional, derivational | Morphology is the study of word formation and structure. Words may undergo different morphological processes which are traditionally classified into two broad groups: derivation and inflection. Derivation is a process in which a new word is created from existing ones, with an adjustment to its meaning and often with a ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The first annotator rated {a} reviews as positive and the rest as negative. The second annotator rated {b} reviews as positive and the rest as negative. 80 reviews were rated as positive by both annotators. Compute the quality of the above reference using Cohen's Kappa.Give your answer as a numerical value to three dec... | Landis and Koch (1977) gave the following table for interpreting κ {\displaystyle \kappa } values for a 2-annotator 2-class example. This table is however by no means universally accepted. They supplied no evidence to support it, basing it instead on personal opinion. It has been noted that these guidelines may be more... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The first annotator rated {a} reviews as positive and the rest as negative. The second annotator rated {b} reviews as positive and the rest as negative. 80 reviews were rated as positive by both annotators. Compute the quality of the above reference using Cohen's Kappa.Give your answer as a numerical value to three dec... | Confusion matrix for two annotators, three categories {Yes, No, Maybe} and 45 items rated (90 ratings for 2 annotators): To calculate the expected agreement, sum marginals across annotators and divide by the total number of ratings to obtain joint proportions. Square and total these: To calculate observed agreement, di... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been publishing a daily column for the Gazette over the last few years and have recently reached a milestone --- your 1000th column! Realizing you'd like to go skiing more often, you decide it might be easier to automate your job by training a story generation system on the columns you've already written. Then... | Recently the rise of transformer models replacing more traditional RNN (LSTM) have provided a flexibility in the mapping of text sequences to text sequences of a different type, which is well suited to automatic summarization. This includes models such as T5 and Pegasus. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been publishing a daily column for the Gazette over the last few years and have recently reached a milestone --- your 1000th column! Realizing you'd like to go skiing more often, you decide it might be easier to automate your job by training a story generation system on the columns you've already written. Then... | The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and published in preprint on OpenAI's website on June 11, 2018. It showed how a generative model of language is able to acquire world knowledge and process long-range dependencies by pre-t... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | The grammar G = ( { S , A , B , C , D } , { a , b , c } , R , S ) {\displaystyle G=(\{S,A,B,C,D\},\{a,b,c\},R,S)} , with productions S → A B & D C {\displaystyle S\rightarrow AB\&DC} , A → a A | ϵ {\displaystyle A\rightarrow aA\ |\ \epsilon } , B → b B c | ϵ {\displaystyle B\rightarrow bBc\ |\ \epsilon } , C → c C | ϵ ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar \(G\) (where \(\text{S}\) is the top-level symbol):
\(R_{01}: \text{S} \rightarrow \text{NP VP}\)
\(R_{02}: \text{NP} \rightarrow \text{NP0}\)
\(R_{03}: \text{NP} \rightarrow \text{Det NP0}\)
\(R_{04}: \text{NP0} \rightarrow \text{N}\)
\(R_{05}: \text{NP0} \rightarrow \text{... | Let us notate a formal grammar as G = ( N , Σ , P , S ) {\displaystyle G=(N,\Sigma ,P,S)} , with N {\displaystyle N} a set of nonterminal symbols, Σ {\displaystyle \Sigma } a set of terminal symbols, P {\displaystyle P} a set of production rules, and S ∈ N {\displaystyle S\in N} the start symbol. A string u ∈ ( N ∪ Σ )... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select all statements that are true.A penalty will be applied for any wrong answers. | In computer languages it is expected that any truth-valued expression be permitted as the selection condition rather than restricting it to be a simple comparison. In SQL, selections are performed by using WHERE definitions in SELECT, UPDATE, and DELETE statements, but note that the selection condition can result in an... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select all statements that are true.A penalty will be applied for any wrong answers. | Then, all result sets returned by the executed statements must be fetched. The MySQL server allows having statements that do return result sets and statements that do not return result sets in one multiple statement. See examples in | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The edit distance between “piece” and “peace” is(Penalty for wrong ticks) | In this case, two remote strings σ A {\displaystyle \sigma _{A}} and σ B {\displaystyle \sigma _{B}} need to be reconciled. Typically, it is assumed that these strings differ by up to a fixed number of edits (i.e. character insertions, deletions, or modifications). Then data synchronization is the process of reducing e... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
The edit distance between “piece” and “peace” is(Penalty for wrong ticks) | Arsenikk:, you seem to have added the length (as 372 km, later changed to 371) with this edit. Do you, or anyone, object to a change to one of the values outlined above? | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
It is often desirable to be able to express the performance of an NLP system in the form of a
single number, which is not the case when the Precision/Recall framework is used.
Indicate what scores can be used to convert Precision/Recall measures into a unique number.
For each score, give the corresponding formula. | Precision and recall are combined using the harmonic mean in the following fashion, with recall weighted 9 times more than precision: F m e a n = 10 P R R + 9 P {\displaystyle F_{mean}={\frac {10PR}{R+9P}}} The measures that have been introduced so far only account for congruity with respect to single words but not wit... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
It is often desirable to be able to express the performance of an NLP system in the form of a
single number, which is not the case when the Precision/Recall framework is used.
Indicate what scores can be used to convert Precision/Recall measures into a unique number.
For each score, give the corresponding formula. | It has been pointed out that precision is usually twinned with recall to overcome this problem , as the unigram recall of this example would be 3 / 6 {\displaystyle 3/6} or 2 / 7 {\displaystyle 2/7} . The problem being that as there are multiple reference translations, a bad translation could easily have an inflated re... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider an HMM Part-of-Speech tagger, the tagset of which contains, among others: DET, N, V, ADV and ADJ, and some of the parameters of which are:
$$
\begin{gathered}
P_{1}(\mathrm{a} \mid \mathrm{DET})=0.1, \quad P_{1}(\text { accurately } \mid \mathrm{ADV})=0.1, \quad P_{1}(\text { computer } \mid \mathrm{N})=0.1, ... | CLAWS, DeRose's and Church's methods did fail for some of the known cases where semantics is required, but those proved negligibly rare. This convinced many in the field that part-of-speech tagging could usefully be separated from the other levels of processing; this, in turn, simplified the theory and practice of comp... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider an HMM Part-of-Speech tagger, the tagset of which contains, among others: DET, N, V, ADV and ADJ, and some of the parameters of which are:
$$
\begin{gathered}
P_{1}(\mathrm{a} \mid \mathrm{DET})=0.1, \quad P_{1}(\text { accurately } \mid \mathrm{ADV})=0.1, \quad P_{1}(\text { computer } \mid \mathrm{N})=0.1, ... | CLAWS, DeRose's and Church's methods did fail for some of the known cases where semantics is required, but those proved negligibly rare. This convinced many in the field that part-of-speech tagging could usefully be separated from the other levels of processing; this, in turn, simplified the theory and practice of comp... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
What are the different types of morphologies that can be considered? Briefly describe the main differences between them. | Functions defined at the morphomic level are of many qualitatively different types. One example is the different ways the perfect participle can be realised in English––sometimes, this form is created through suffixation, as in bitten and packed, sometimes through a process of ablaut, as in sung, and sometimes through ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
What are the different types of morphologies that can be considered? Briefly describe the main differences between them. | TARs also exhibit a range of morphologies, which are interpreted as representing different formative and evolutionary processes. Past efforts have been made to categorize TAR with classification systems primarily focusing on crest morphology. *Established in the literature but not recognized as a distinct morphology | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar, where S is the top-level symbol, upper-case letters denotes non-terminals and lower case letters denotes terminals:S → T A
S → B A
S → A B
S → b
A → A C
A → a
T → A B
B → b
C → c
Except the first one, the next questions are based on filling the cells of the chart used b... | The grammar uses these terminal symbols but does not define them. They are always leaf nodes (at the bottom bushy end) of the parse tree. The capitalized terms like Sums are nonterminal symbols. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following context-free grammar, where S is the top-level symbol, upper-case letters denotes non-terminals and lower case letters denotes terminals:S → T A
S → B A
S → A B
S → b
A → A C
A → a
T → A B
B → b
C → c
Except the first one, the next questions are based on filling the cells of the chart used b... | The grammar uses these terminal symbols but does not define them. They are always at the bottom bushy end of the parse tree. The capitalized terms like Sums are nonterminal symbols. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In the above, what is the chance agreement between the two annotators?Give your answer as a numerical value to three decimal places. | Confusion matrix for two annotators, three categories {Yes, No, Maybe} and 45 items rated (90 ratings for 2 annotators): To calculate the expected agreement, sum marginals across annotators and divide by the total number of ratings to obtain joint proportions. Square and total these: To calculate observed agreement, di... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
In the above, what is the chance agreement between the two annotators?Give your answer as a numerical value to three decimal places. | {\displaystyle \ {\frac {1}{(1+j\omega {\hat {\tau _{1}}})(1+j\omega {\hat {\tau _{2}}})}}\ .} Of course agreement is good when the assumption τ1 >> τ2 is accurate. | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. Give four standard measures usually considered for the evaluation of such a system? Explain their meaning. B... | "This is a benefit because it provides an unbiased method of performance evaluation and prevents the interference of a manager's feelings in an employee's review" (Mishra and Crampton, 1998). Management can review an employee's performance by checking the surveillance to detect and potentially prevent problems". Email ... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
You have been hired to evaluate an email monitoring system aimed at detecting potential security issues. The targeted goal of the application is to decide whether a given email should be further reviewed or not. Give four standard measures usually considered for the evaluation of such a system? Explain their meaning. B... | Common Criteria evaluations are performed on computer security products and systems. Target of Evaluation (TOE) – the product or system that is the subject of the evaluation. The evaluation serves to validate claims made about the target. To be of practical use, the evaluation must verify the target's security features... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following toy corpus: the cat cut the hat
What is the probability of the following sequences, if the parameters are estimated using MLE
(maximum-likelihood estimation) on the above corpus (make use of a calculator or even a
short program):
- cutthechat
- cut the chat
Fully justify your answer. | A statistical tagger looks for the most probable tag for an ambiguously tagged text σ σ … σ {\displaystyle \sigma \sigma \ldots \sigma }: γ ∗ … γ ∗ = arg m a x γ ∈ T ( σ ) p ( γ … γ σ … σ ) {\displaystyle \gamma ^{*}\ldots \gamma ^{*}=\operatorname {\arg \,max} _{\gamma \in T(\sigma )}p(\gamma \ldots \gamm... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Consider the following toy corpus: the cat cut the hat
What is the probability of the following sequences, if the parameters are estimated using MLE
(maximum-likelihood estimation) on the above corpus (make use of a calculator or even a
short program):
- cutthechat
- cut the chat
Fully justify your answer. | Let c ( w , w ′ ) {\displaystyle c(w,w')} be the number of occurrences of the word w {\displaystyle w} followed by the word w ′ {\displaystyle w'} in the corpus. The equation for bigram probabilities is as follows: p K N ( w i | w i − 1 ) = max ( c ( w i − 1 , w i ) − δ , 0 ) ∑ w ′ c ( w i − 1 , w ′ ) + λ w i − 1 p K N... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select which statements are true about the CYK algorithm.A penalty will be applied for any incorrect answers. | Note that the term 'CYK algorithm' describes the CYK variant of the inside algorithm that finds an optimal parse tree for a sequence using a PCFG. It extends the actual CYK algorithm used in non-probabilistic CFGs.The inside algorithm calculates α ( i , j , v ) {\displaystyle \alpha (i,j,v)} probabilities for all i , j... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select which statements are true about the CYK algorithm.A penalty will be applied for any incorrect answers. | This either leads to a contradiction and a backtracking step, or, if no contradiction is derived, it follows that the choice was a correct one that leads to a satisfying assignment. Therefore, the algorithm either correctly finds a satisfying assignment or it correctly determines that the input is unsatisfiable.Even et... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select all statements that are true.A penalty will be applied for any wrong answers. | In computer languages it is expected that any truth-valued expression be permitted as the selection condition rather than restricting it to be a simple comparison. In SQL, selections are performed by using WHERE definitions in SELECT, UPDATE, and DELETE statements, but note that the selection condition can result in an... | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
Select all statements that are true.A penalty will be applied for any wrong answers. | Then, all result sets returned by the executed statements must be fetched. The MySQL server allows having statements that do return result sets and statements that do not return result sets in one multiple statement. See examples in | https://www.kaggle.com/datasets/conjuring92/wiki-stem-corpus |
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