nc33/MultiSpan_SQUAD huggingface dataset:
Law_of_the_United_States

Generally, American civil procedure has several notable features, including extensive pretrial discovery, heavy reliance on live testimony obtained at deposition or elicited in front of a jury, and aggressive pretrial "law and motion" practice designed to result in a pretrial disposition (that is, summary judgment) or a settlement. U.S. courts pioneered the concept of the opt-out class action, by which the burden falls on class members to notify the court that they do not wish to be bound by the judgment, as opposed to opt-in class actions, where class members must join into the class. Another unique feature is the so-called American Rule under which parties generally bear their own attorneys' fees (as opposed to the English Rule of "loser pays"), though American legislators and courts have carved out numerous exceptions.

Question: What is extensive pretrial discovery a part of?
Answer: American civil procedure

Question: What is a pretrial deposition?
Answer: summary judgment

Question: What is an opt-out class action?
Answer: the burden falls on class members to notify the court that they do not wish to be bound by the judgment

Question: What is an opt-in class action?
Answer: class members must join into the class

Question: What is the American Rule?
Answer: parties generally bear their own attorneys' fees
Law_of_the_United_States

Criminal law involves the prosecution by the state of wrongful acts which are considered to be so serious that they are a breach of the sovereign's peace (and cannot be deterred or remedied by mere lawsuits between private parties). Generally, crimes can result in incarceration, but torts (see below) cannot. The majority of the crimes committed in the United States are prosecuted and punished at the state level. Federal criminal law focuses on areas specifically relevant to the federal government like evading payment of federal income tax, mail theft, or physical attacks on federal officials, as well as interstate crimes like drug trafficking and wire fraud.

Question: What is criminal law?
Answer: prosecution by the state of wrongful acts

Question: What type of wrongful act will the state prosecute?
Answer: acts which are considered to be so serious that they are a breach of the sovereign's peace

Question: Who focuses on things such as evading payment of federal income tax, mail theft, or physical attacks on federal officials, as well as interstate crimes like drug trafficking and wire fraud?
Answer: Federal criminal law

Question: Where are the majority of the U.S.'s crimes prosecuted?
Answer: state level

Question: What can result in incarceration?
Answer: crimes
Law_of_the_United_States

Some states distinguish between two levels: felonies and misdemeanors (minor crimes). Generally, most felony convictions result in lengthy prison sentences as well as subsequent probation, large fines, and orders to pay restitution directly to victims; while misdemeanors may lead to a year or less in jail and a substantial fine. To simplify the prosecution of traffic violations and other relatively minor crimes, some states have added a third level, infractions. These may result in fines and sometimes the loss of one's driver's license, but no jail time.

Question: What two levels of crime are there?
Answer: felonies and misdemeanors

Question: What is a misdemeanor?
Answer: minor crimes

Question: What results in lengthy prison sentences as well as subsequent probation, large fines, and orders to pay restitution directly to victims?
Answer: felony convictions

Question: What usually happens with misdemeanors?
Answer: a year or less in jail and a substantial fine

Question: What is a third level of crime that some states have adopted?
Answer: infractions
Law_of_the_United_States

Contract law covers obligations established by agreement (express or implied) between private parties. Generally, contract law in transactions involving the sale of goods has become highly standardized nationwide as a result of the widespread adoption of the Uniform Commercial Code. However, there is still significant diversity in the interpretation of other kinds of contracts, depending upon the extent to which a given state has codified its common law of contracts or adopted portions of the Restatement (Second) of Contracts.

Question: What is contract law?
Answer: obligations established by agreement (express or implied) between private parties

Question: What standardized contract law?
Answer: Uniform Commercial Code

Question: What kinds of agreements do contract law cover?
Answer: express or implied
Data_compression

In signal processing, data compression, source coding, or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying unnecessary information and removing it. The process of reducing the size of a data file is referred to as data compression. In the context of data transmission, it is called source coding (encoding done at the source of the data before it is stored or transmitted) in opposition to channel coding.

Question: What involves encoding information using fewer bits than the original representation?
Answer: data compression

Question: What can be either lossy or lossless?
Answer: Compression

Question: What reduces bits by identifying and eliminating statistical redundancy? 
Answer: Lossless compression

Question: What is the process called of reducing the size of a data file?
Answer: data compression

Question: What is the process called of encoding at the source of the data before it's processed?
Answer: source coding
Data_compression

Compression is useful because it helps reduce resource usage, such as data storage space or transmission capacity. Because compressed data must be decompressed to use, this extra processing imposes computational or other costs through decompression; this situation is far from being a free lunch. Data compression is subject to a space–time complexity trade-off. For instance, a compression scheme for video may require expensive hardware for the video to be decompressed fast enough to be viewed as it is being decompressed, and the option to decompress the video in full before watching it may be inconvenient or require additional storage. The design of data compression schemes involves trade-offs among various factors, including the degree of compression, the amount of distortion introduced (when using lossy data compression), and the computational resources required to compress and decompress the data.

Question: What helps reduce resource usage?
Answer: Compression

Question: What must be decompressed? 
Answer: compressed data

Question: What is subject to a space-time complexity trade off? 
Answer: Data compression

Question: What type of scheme involves trade offs among other things?
Answer: data compression
Data_compression

Lossless data compression algorithms usually exploit statistical redundancy to represent data without losing any information, so that the process is reversible. Lossless compression is possible because most real-world data exhibits statistical redundancy. For example, an image may have areas of colour that do not change over several pixels; instead of coding "red pixel, red pixel, ..." the data may be encoded as "279 red pixels". This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy.

Question: What usually exploits statistical redundancy?
Answer: Lossless data compression algorithms

Question: What represents statistical redundancy?
Answer: Lossless compression

Question: What may have colors that do not change over several pixels?
Answer: an image
Data_compression

The Lempel–Ziv (LZ) compression methods are among the most popular algorithms for lossless storage. DEFLATE is a variation on LZ optimized for decompression speed and compression ratio, but compression can be slow. DEFLATE is used in PKZIP, Gzip and PNG. LZW (Lempel–Ziv–Welch) is used in GIF images. Also noteworthy is the LZR (Lempel-Ziv–Renau) algorithm, which serves as the basis for the Zip method.[citation needed] LZ methods use a table-based compression model where table entries are substituted for repeated strings of data. For most LZ methods, this table is generated dynamically from earlier data in the input. The table itself is often Huffman encoded (e.g. SHRI, LZX). Current LZ-based coding schemes that perform well are Brotli and LZX. LZX is used in Microsoft's CAB format.

Question: What compression methods are among the most popular?
Answer: Lempel–Ziv (LZ)

Question: What is used in PKZIP, Gzip and PNG?
Answer: DEFLATE

Question: What serves as the basis of the Zip method?
Answer: LZR

Question: What is a current LZ based coding scheme that does well?
Answer: Brotli

Question: What is used in Microsoft's CAB format?
Answer: LZX
Data_compression

In a further refinement of the direct use of probabilistic modelling, statistical estimates can be coupled to an algorithm called arithmetic coding. Arithmetic coding is a more modern coding technique that uses the mathematical calculations of a finite-state machine to produce a string of encoded bits from a series of input data symbols. It can achieve superior compression to other techniques such as the better-known Huffman algorithm. It uses an internal memory state to avoid the need to perform a one-to-one mapping of individual input symbols to distinct representations that use an integer number of bits, and it clears out the internal memory only after encoding the entire string of data symbols. Arithmetic coding applies especially well to adaptive data compression tasks where the statistics vary and are context-dependent, as it can be easily coupled with an adaptive model of the probability distribution of the input data. An early example of the use of arithmetic coding was its use as an optional (but not widely used) feature of the JPEG image coding standard. It has since been applied in various other designs including H.264/MPEG-4 AVC and HEVC for video coding.

Question: What can be paired with an algorithm called arithmetic coding?
Answer: statistical estimates

Question: What can achieve superior compression?
Answer: Arithmetic coding

Question: What uses an internal memory state?
Answer: Huffman algorithm
Data_compression

Lossy data compression is the converse of lossless data compression. In these schemes, some loss of information is acceptable. Dropping nonessential detail from the data source can save storage space. Lossy data compression schemes are designed by research on how people perceive the data in question. For example, the human eye is more sensitive to subtle variations in luminance than it is to the variations in color. JPEG image compression works in part by rounding off nonessential bits of information. There is a corresponding trade-off between preserving information and reducing size. A number of popular compression formats exploit these perceptual differences, including those used in music files, images, and video.

Question: What type of data compression is the converse of lossless date data compression?
Answer: Lossy

Question: What can save storage space?
Answer: Dropping nonessential detail from the data source

Question: What helps by eliminating off nonessential bits of information?
Answer: JPEG image compression
Data_compression

In lossy audio compression, methods of psychoacoustics are used to remove non-audible (or less audible) components of the audio signal. Compression of human speech is often performed with even more specialized techniques; speech coding, or voice coding, is sometimes distinguished as a separate discipline from audio compression. Different audio and speech compression standards are listed under audio coding formats. Voice compression is used in internet telephony, for example, audio compression is used for CD ripping and is decoded by the audio players.

Question: What is used for CD ripping?
Answer: audio compression

Question: What methods are used to remove non-audible components of audio signals?
Answer: psychoacoustics

Question: What compression is usually performed with even more specialized techniques?
Answer: human speech

Question: What is used in internet telephony? 
Answer: Voice compression

Question: What is encoded by audio players?
Answer: audio compression
Data_compression

There is a close connection between machine learning and compression: a system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression (by using arithmetic coding on the output distribution) while an optimal compressor can be used for prediction (by finding the symbol that compresses best, given the previous history). This equivalence has been used as a justification for using data compression as a benchmark for "general intelligence."

Question: What is Machine learning closely related to?
Answer: compression

Question: What type of compressor can be used for prediction?
Answer: optimal

Question: What has been used as a benchmark for "general intelligence"?
Answer: data compression
Data_compression

Data compression can be viewed as a special case of data differencing: Data differencing consists of producing a difference given a source and a target, with patching producing a target given a source and a difference, while data compression consists of producing a compressed file given a target, and decompression consists of producing a target given only a compressed file. Thus, one can consider data compression as data differencing with empty source data, the compressed file corresponding to a "difference from nothing." This is the same as considering absolute entropy (corresponding to data compression) as a special case of relative entropy (corresponding to data differencing) with no initial data.

Question: What can be looked at as a special case of data differencing? 
Answer: Data compression

Question: What is made up of producing a difference given a source and a target?
Answer: Data differencing

Question: What can classified as data differencing with empty source data?
Answer: data compression
Data_compression

Audio data compression, not to be confused with dynamic range compression, has the potential to reduce the transmission bandwidth and storage requirements of audio data. Audio compression algorithms are implemented in software as audio codecs. Lossy audio compression algorithms provide higher compression at the cost of fidelity and are used in numerous audio applications. These algorithms almost all rely on psychoacoustics to eliminate less audible or meaningful sounds, thereby reducing the space required to store or transmit them.

Question: What has the potential to reduce the transmission bandwidth and storage requirements of audio data?
Answer: Audio data compression

Question: What is inserted in software as audio codecs?
Answer: Audio compression algorithms

Question: What compression algorithms provide higher compression at the cost of fidelity?
Answer: Lossy
Data_compression

Lossless audio compression produces a representation of digital data that decompress to an exact digital duplicate of the original audio stream, unlike playback from lossy compression techniques such as Vorbis and MP3. Compression ratios are around 50–60% of original size, which is similar to those for generic lossless data compression. Lossless compression is unable to attain high compression ratios due to the complexity of waveforms and the rapid changes in sound forms. Codecs like FLAC, Shorten and TTA use linear prediction to estimate the spectrum of the signal. Many of these algorithms use convolution with the filter [-1 1] to slightly whiten or flatten the spectrum, thereby allowing traditional lossless compression to work more efficiently. The process is reversed upon decompression.

Question: What produces a representation of digital data that decompresses?
Answer: Lossless audio compression

Question: What compression cannot attain high compression ratios?
Answer: Lossless

Question: What are around 50-60% of the original size?
Answer: Compression ratios
Data_compression

Lossy audio compression is used in a wide range of applications. In addition to the direct applications (mp3 players or computers), digitally compressed audio streams are used in most video DVDs, digital television, streaming media on the internet, satellite and cable radio, and increasingly in terrestrial radio broadcasts. Lossy compression typically achieves far greater compression than lossless compression (data of 5 percent to 20 percent of the original stream, rather than 50 percent to 60 percent), by discarding less-critical data.

Question: What compression is used in a lot of applications?
Answer: Lossy

Question: What is used in most video DVDs?
Answer: digitally compressed audio streams

Question: What compression usually achieves far greater compression then lossless? 
Answer: Lossy
Data_compression

To determine what information in an audio signal is perceptually irrelevant, most lossy compression algorithms use transforms such as the modified discrete cosine transform (MDCT) to convert time domain sampled waveforms into a transform domain. Once transformed, typically into the frequency domain, component frequencies can be allocated bits according to how audible they are. Audibility of spectral components calculated using the absolute threshold of hearing and the principles of simultaneous masking—the phenomenon wherein a signal is masked by another signal separated by frequency—and, in some cases, temporal masking—where a signal is masked by another signal separated by time. Equal-loudness contours may also be used to weight the perceptual importance of components. Models of the human ear-brain combination incorporating such effects are often called psychoacoustic models.

Question: What may be used to weight the importance of components?
Answer: Equal-loudness contours

Question: What are often called psychoacoustic models?
Answer: Models of the human ear-brain

Question: What is the process called when a signal is masked by another signal separated by time?
Answer: temporal masking
Data_compression

Other types of lossy compressors, such as the linear predictive coding (LPC) used with speech, are source-based coders. These coders use a model of the sound's generator (such as the human vocal tract with LPC) to whiten the audio signal (i.e., flatten its spectrum) before quantization. LPC may be thought of as a basic perceptual coding technique: reconstruction of an audio signal using a linear predictor shapes the coder's quantization noise into the spectrum of the target signal, partially masking it.

Question: What is the coding called that is used with speech?
Answer: linear predictive coding

Question: What is thought of as a basic perceptual coding technique?
Answer: linear predictive coding

Question: What uses a model of the sound's generator? 
Answer: source-based coders
Data_compression

Latency results from the methods used to encode and decode the data. Some codecs will analyze a longer segment of the data to optimize efficiency, and then code it in a manner that requires a larger segment of data at one time to decode. (Often codecs create segments called a "frame" to create discrete data segments for encoding and decoding.) The inherent latency of the coding algorithm can be critical; for example, when there is a two-way transmission of data, such as with a telephone conversation, significant delays may seriously degrade the perceived quality.

Question: What results from methods used to encode and decode data?
Answer: Latency

Question: What analyzes a statement of data to boost performance?
Answer: codecs

Question: What creates segments called a "frame"?
Answer: codecs
Data_compression

A literature compendium for a large variety of audio coding systems was published in the IEEE Journal on Selected Areas in Communications (JSAC), February 1988. While there were some papers from before that time, this collection documented an entire variety of finished, working audio coders, nearly all of them using perceptual (i.e. masking) techniques and some kind of frequency analysis and back-end noiseless coding. Several of these papers remarked on the difficulty of obtaining good, clean digital audio for research purposes. Most, if not all, of the authors in the JSAC edition were also active in the MPEG-1 Audio committee.

Question: What was published in the IEEE Journal in 1988?
Answer: literature compendium

Question: What did the literature compendium document?
Answer: finished, working audio coders

Question: Where were most of the authors in the JSAC edition?
Answer: MPEG-1 Audio committee
Data_compression

The majority of video compression algorithms use lossy compression. Uncompressed video requires a very high data rate. Although lossless video compression codecs perform at a compression factor of 5-12, a typical MPEG-4 lossy compression video has a compression factor between 20 and 200. As in all lossy compression, there is a trade-off between video quality, cost of processing the compression and decompression, and system requirements. Highly compressed video may present visible or distracting artifacts.

Question: What all mostly use lossy compression?
Answer: video compression algorithms

Question: What requires a high data rate?
Answer: Uncompressed video

Question: What may present visible or distracting artifacts?
Answer: Highly compressed video
Data_compression

Some video compression schemes typically operate on square-shaped groups of neighboring pixels, often called macroblocks. These pixel groups or blocks of pixels are compared from one frame to the next, and the video compression codec sends only the differences within those blocks. In areas of video with more motion, the compression must encode more data to keep up with the larger number of pixels that are changing. Commonly during explosions, flames, flocks of animals, and in some panning shots, the high-frequency detail leads to quality decreases or to increases in the variable bitrate.

Question: What compression typically operate on square-shaped groups of pixels?
Answer: video

Question: What only sends the differences within those pixels and blocks?
Answer: macroblocks

Question: What does high-frequency detail lead to?
Answer: variable bitrate
Data_compression

Video data may be represented as a series of still image frames. The sequence of frames contains spatial and temporal redundancy that video compression algorithms attempt to eliminate or code in a smaller size. Similarities can be encoded by only storing differences between frames, or by using perceptual features of human vision. For example, small differences in color are more difficult to perceive than are changes in brightness. Compression algorithms can average a color across these similar areas to reduce space, in a manner similar to those used in JPEG image compression. Some of these methods are inherently lossy while others may preserve all relevant information from the original, uncompressed video.

Question: What may be represented as a series of still image frames?
Answer: Video data

Question: What can average a color across similar areas to reduce space?
Answer: Compression algorithms

Question: What is hard to tell with smaller differences involved?
Answer: color