DataHammer/scimrc huggingface dataset:
Question: What are the three translation models they propose?
Evidence: Neural machine translation (NMT) is popularly implemented as an encoder-decoder framework BIBREF0, in which the encoder is right in charge of source sentence representation. Typically, the input sentence is implicitly represented as a contextualized source representation through deep learning networks. By further feeding the decoder, the source representation is used to learn dependent time-step context vectors for predicting target translation BIBREF1.
In state-of-the-art Transformer-based encoder, self-attention mechanisms are good at capturing the general information in a sentence BIBREF2, BIBREF3, BIBREF4. However, it is difficult to distinguish which kind of information lying deeply under the language is really salient for learning source representation. Intuitively, when a person reads a source sentence, he/she often selectively focuses on the basic sentence meaning, and re-reads the entire sentence to understand its meaning completely. Take the English sentence in Table TABREF2 as an example. We manually annotate its basic meaning as a shorter sequence of words than in the original sentence, called backbone information. Obviously, these words with the basic meaning contain more important information for human understanding than the remaining words in the sentence. We argue that such backbone information is also helpful for learning source representation, and is not explicitly considered by the existing NMT system to enrich the source sentence representation.
In this paper, we propose a novel explicit sentence compression approach to enhance the source representation for NMT. To this end, we first design three sentence compression models to accommodate the needs of various languages and scenarios, including supervised, unsupervised, and semi-supervised ways, to learn a backbone information words sequence (as shown in Table TABREF2) from the source sentence. We then propose three translation models, including backbone source-side fusion based NMT (BSFNMT), backbone target-side fusion (BTFNMT), and both-side fusion based NMT (BBFNMT), to introduce this backbone knowledge into the existing Transformer NMT system for improving translation predictions. Empirical results on the WMT14 English-to-German and English-to-French translation tasks show that the proposed approach significantly improves the translation performance over the strong even state-of-the-art NMT baselines.
We then propose three translation models, including backbone source-side fusion based NMT (BSFNMT), backbone target-side fusion (BTFNMT), and both-side fusion based NMT (BBFNMT), to introduce this backbone knowledge into the existing Transformer NMT system for improving translation predictions.
Answer: Backbone source-side fusion based NMT (BSFNMT), backbone target-side fusion (BTFNMT), and both-side fusion based NMT (BBFNMT).
Question: Who invented the first car?
Answer: Karl Benz invented the first car in 1896 AD.  It was a petrol-powered engine designed to travel slowly. Made entirely by hand, the number of cars on roads did not surge as the supply was limited. However, the first popular car was the Model T, built-in 1908 by Ford in the USA.  Ford sold over 15 million units of Model T worldwide.
Question: Explain the best way to swing a golf iron compared to a golf driver.
Answer: When hitting an iron you want to make a downward striking motion in the grass. The driver is more of a sweeping motion through the ball. Overall, shorten the back swing on the driver and it will help gain control.
Question: Which district is Lightwater in?
Evidence: Lightwater is a village in the Surrey Heath district of Surrey, England, about 27 miles (43 km) southwest of central London. Immediately surrounding towns and villages include Bagshot, Deepcut, Windlesham, Camberley, and West End, Woking. It is bounded to the north-west by the M3 motorway and to the north-east by the "Lightwater Bypass" (A322). To the south-east it is bounded by the "Red Road" (B311), while to the south-west there are vehicle-testing tracks owned by the Ministry of Defence.

The village is adjacent to junction 3 of the M3 motorway. The nearest railway station is at Bagshot, on the line between Ascot and Aldershot. Lightwater is part of the civil parish of Windlesham, which has a population of 17,000 and also includes the neighbouring village of Bagshot.
Answer: Lightwater is in Surrey Heath district in Surrey. It is in the civil parish of Windlesham.
Question: How many scenarios did the authors evaluate?
Evidence: This section presents experiments conducted on the annotated corpora introduced in section SECREF4 . We put the main focus on identifying argument components in the discourse. To comply with the machine learning terminology, in this section we will use the term domain as an equivalent to a topic (remember that our dataset includes six different topics; see section SECREF38 ).
We evaluate three different scenarios. First, we report ten-fold cross validation over a random ordering of the entire data set. Second, we deal with in-domain ten-fold cross validation for each of the six domains. Third, in order to evaluate the domain portability of our approach, we train the system on five domains and test on the remaining one for all six domains (which we report as cross-domain validation).
We evaluate three different scenarios.
Answer: three
Question: Why is Brazilian jiu jitsu an excellent martial art?
Answer: Brazilian jiu jitsu (BJJ) is an excellent martial art for a number of reasons.  BJJ is, first and foremost, a generally safe martial art.  BJJ does not emphasize or focus on striking techniques like punching and kicking, rather, BJJ focuses on use of leverage and body mechanics to control and subdue an opponent.  BJJ is accessible to almost anyone regardless of age, sex, or fitness level as the practitioner can determine how relaxed or aggressive to be during practicing the art.  BJJ is an excellent form of exercise and promotes cardiovascular fitness, flexibility, strength, endurance, and an overall sense of well-being.  Further, there are approaches to BJJ that resonate with people who are casual hobbyists as well as those that seek international competition- and all levels of studends across that spectru.  BJJ is easily a life-long endeavor that is safe, engaging, and also an excellent complement to striking based martial arts such as karate, kickboxing, and boxing.
Question: Write an friendly, convincing e-mail to my landlord asking whether I can get a dog.
Answer: Dear Sir/Madam,

I hope this email finds you well.
I'm reaching out with a request regarding the property I rent from you. I'm interested in getting myself a dog and I noticed there wasn't a clause in our rental agreement specifying if this was allowed or not so I would like to consult you about that.
I work from home most days of the week and have a very laidback lifestyle, so I'm looking for a dog that can keep me company but also take me out of the house for walks. I'm looking into a small breed that is also calm and friendly - likely a french bulldog. They are easy to train and known for spending most of their day sleeping, this is also a very quiet breed that doesn't have a lot of complains of barking.
Is that something you would permit? 
I am also happy to hop on a call or meet in person to discuss further in case you have any follow-up questions.

Looking forward to hearing from you soon.

Kind regards
Question: From the below text extract the year and list all movies released in that year separated by a comma in the form {Year} - {all movies released in that year} and show this as a bullet list
Evidence: Commercial Hindi cinema grew in the 1980s, with films such as Ek Duuje Ke Liye (1981), Disco Dancer (1982), Himmatwala (1983), Tohfa (1984), Naam (1986), Mr India (1987), and Tezaab (1988).

In the late 1980s,[timeframe?] Hindi cinema experienced another period of stagnation, with a decline in box office turnout, due to increasing violence, decline in musical melodic quality, and rise in video piracy, leading to middle-class family audiences abandoning theatres. The turning point came with Indian blockbuster Disco Dancer (1982) which began the era of disco music in Indian cinema. Lead actor Mithun Chakraborty and music director Bappi Lahiri had the highest number of mainstream Indian hit movies that decade. At the end of the decade, Yash Chopra's Chandni (1989) created a new formula for Bollywood musical romance films, reviving the genre and defining Hindi cinema in the years that followed. Commercial Hindi cinema grew in the late 1980s and 1990s, with the release of Mr. India (1987), Qayamat Se Qayamat Tak (1988), Chaalbaaz (1989), Maine Pyar Kiya (1989), Lamhe (1991), Saajan (1991), Khuda Gawah (1992), Khalnayak (1993), Darr (1993), Hum Aapke Hain Koun..! (1994), Dilwale Dulhaniya Le Jayenge (1995), Dil To Pagal Hai (1997), Pyar Kiya Toh Darna Kya (1998) and Kuch Kuch Hota Hai (1998). Cult classic Bandit Queen (1994) directed by Shekhar Kapur received international recognition and controversy.
Answer: Here are the years and the movies released in that year from the given text:
1981 - Ek Duuje Ke Liye
1982 - Disco Dancer 
1983 - Himmatwala
1984 - Tohfa
1986 - Naam
1987 - Mr India
1988 - Tezaab, Qayamat Se Qayamat Tak, 
1989 - Chandni, Chaalbaaz, Maine Pyar Kiya
1991 - Lamhe, Saajan
1992 - Khuda Gawah
1993 - Khalnayak, Darr
1994 - Hum Aapke Hain Koun..!, Bandit Queen
1995 - Dilwale Dulhaniya Le Jayenge
1997 - Dil To Pagal Hai
1998 - Pyar Kiya Toh Darna Kya, Kuch Kuch Hota Hai
Question: How do cardiac pacemakers work?
Evidence: Modern pacemakers usually have multiple functions. The most basic form monitors the heart's native electrical rhythm. When the pacemaker wire or "lead" does not detect heart electrical activity in the chamber – atrium or ventricle – within a normal beat-to-beat time period – most commonly one second – it will stimulate either the atrium or the ventricle with a short low voltage pulse. If it does sense electrical activity, it will hold off stimulating. This sensing and stimulating activity continues on a beat by beat basis and is called "demand pacing". In the case of a dual-chamber device, when the upper chambers have a spontaneous or stimulated activation, the device starts a countdown to ensure that in an acceptable – and programmable – interval, there is an activation of the ventricle, otherwise again an impulse will be delivered.
Answer: Pacemakers or cardiac pacemakers usually refer to artificial cardiac pacemakers, since our body has a natural cardiac pacemaker. 

The artificial cardiac pacemakers work by detecting electric signals through the conductive leads that are attached to the inside of heart walls, usually in atriums, and, in the absence of an electrical signal, generate one to stimulate the desired heart area, either an atrium or a ventricle.
Question: Without quoting directly from the text, briefly describe how the United Kingdom was formed from its constituent countries.
Evidence: The British monarchy traces its origins from the petty kingdoms of Anglo-Saxon England and early medieval Scotland, which consolidated into the kingdoms of England and Scotland by the 10th century. England was conquered by the Normans in 1066, after which Wales also gradually came under the control of Anglo-Normans. The process was completed in the 13th century when the Principality of Wales became a client state of the English kingdom. Meanwhile, Magna Carta began the process of reducing the English monarch's political powers. In the 16th century, English and Scottish monarchs played a central role in what became the religious English Reformation and Scottish Reformation. From 1603, the English and Scottish kingdoms were ruled by a single sovereign. From 1649 to 1660, the tradition of monarchy was broken by the republican Commonwealth of England, which followed the Wars of the Three Kingdoms. Following the installation of William III and Mary II as co-monarchs in the Glorious Revolution, the Bill of Rights 1689, and its Scottish counterpart the Claim of Right Act 1689, further curtailed the power of the monarchy and excluded Roman Catholics from succession to the throne. In 1707, the kingdoms of England and Scotland were merged to create the Kingdom of Great Britain, and in 1801, the Kingdom of Ireland joined to create the United Kingdom of Great Britain and Ireland. The British monarch was the nominal head of the vast British Empire, which covered a quarter of the world's land area at its greatest extent in 1921.
Answer: The United Kingdom is now made up of England, Wales, Scotland and Northern Ireland. These countries were finally united in 1801, after England and Scotland (which had merged in 1707) were joined by the Kingdom of Ireland.
Question: Which is a species of fish? Blowfish or Toucan
Answer: Blowfish
Question: Given this paragraph about speed limits, what was first law regulating speed limits in UK, when was it enacted and what speed limits it set.
Evidence: The use of speed limits predates both motorized vehicles, and enforcement of the laws. Facing the invention of the automobile, many nations enacted speed limit laws, and appropriate measures to enforce them. The Locomotive Acts in the UK set speed limits for vehicles, and later codified enforcement methods. The first Locomotive Act, passed in 1861, set a speed limit of 10 miles per hour (16 km/h) in uninhabited areas, and 5 miles per hour (8.0 km/h) within towns. This act also included the value of fines for violations of the law.
Answer: The first speed limit law in UK was called Locomotive Act, passed in 1861, set a speed limit of 10 miles per hour (16 km/h) in uninhabited areas, and 5 miles per hour (8.0 km/h) within towns.
Question: What is an interchange fee?
Answer: Interchange fee is a term used in the payment card industry to describe a fee paid between banks for the acceptance of card-based transactions. Usually for sales/services transactions it is a fee that a merchant's bank (the "acquiring bank") pays a customer's bank (the "issuing bank").

In a credit card or debit card transaction, the card-issuing bank in a payment transaction deducts the interchange fee from the amount it pays the acquiring bank that handles a credit or debit card transaction for a merchant. The acquiring bank then pays the merchant the amount of the transaction minus both the interchange fee and an additional, usually smaller, fee for the acquiring bank or independent sales organization (ISO), which is often referred to as a discount rate, an add-on rate, or passthru. For cash withdrawal transactions at ATMs, however, the fees are paid by the card-issuing bank to the acquiring bank (for the maintenance of the machine).
Question: What is the significance of Glasgow, Georgia?
Evidence: A post office called Glasgow was established in 1853, and remained in operation until 1905.The community was named after Glasgow, in Scotland, the ancestral home of a large share of the first settlers.
Answer: It is a community named after Glasgow in Scotland which is the ancestral home of a large part of the first settlers.
Question: Help me understand how I would grow a garden in my backyard
Answer: Growing a garden in your backyard requires yearlong dedication. Gardens can be composed of a variety of different types of plants and trees, depending on the size of the garden. Some plants are seasonal and must be re-planted every year. To plant such plants in your backyard, you will need to plant them usually in the winter or spring seasons. Then, you will need to regularly water those plants so that they bloom. Other plants and trees can be planted once and continue to grow year-round. These kinds of trees need to only be planted once and cared for regularly with water and fertilizer.
Question: What does Lady Gaga affectionately call her fans?
Answer: Little monsters.
Question: What empirical data are the Blending Game predictions compared to?
Evidence: In this paper we have investigated duality of patterning at the lexicon level. We have quantified in particular the notions of combinatoriality and compositionality as observed in real languages as well as in a large-scale dataset produced in the framework of a web-based word association experiment BIBREF1 . We have paralleled this empirical analysis with a modeling scheme, the Blending Game, whose aim is that of identifying the main determinants for the emergence of duality of patterning in language. We analyzed the main properties of the lexicon emerged from the Blending Game as a function of the two parameters of the model, the graph connectivity $p_{link}$ and the memory scale $\tau $ . We found that properties of the emerging lexicon related to the combinatoriality, namely the words length distribution, the frequency of use of the different forms and a measure for the combinatoriality itself, reflect both qualitatively and quantitatively the corresponding properties as measured in human languages, provided that the memory parameter $\tau $ is sufficiently high, that is that a sufficiently high effort is required in order to understand and learn brand new forms. Conversely, the compositional properties of the lexicon are related to the parameter $p_{link}$ , that is a measure of the level of structure of the conceptual graph. For intermediate and low values of $p_{link}$ , semantic relations between objects are more differentiated with respect to the situation of a more dense graph, in which every object is related to anyone else, and compositionality is enhanced. In summary, while the graph connectivity strongly affects the compositionality of the lexicon, noise in communication strongly affects the combinatoriality of the lexicon.
We found that properties of the emerging lexicon related to the combinatoriality, namely the words length distribution, the frequency of use of the different forms and a measure for the combinatoriality itself, reflect both qualitatively and quantitatively the corresponding properties as measured in human languages, provided that the memory parameter $\tau $ is sufficiently high, that is that a sufficiently high effort is required in order to understand and learn brand new forms.
Answer: The answers are shown as follows:
* words length distribution, the frequency of use of the different forms and a measure for the combinatoriality
Question: What are the five MLB teams with the most World Series wins in descending order?
Answer: New York Yankees, St. Louis Cardinals, Oakland Athletics, Boston Red Sox, San Francisco Giants
Question: How Can I become a Referee?
Answer: To become a Football Association (FA) referee you need to be at least 14-years-old and a resident in England. Contact your County FA for further information.

Note: You would need to attend a Basic Referees Course with your local County FA to train as a qualified referee.
Question: Which of the big five is the most dangerous animals in Africa ?
Answer: The African Buffalo is notorious for killing the most number of hunters.
Question: What languages are represented in the dataset?
Evidence: FLOAT SELECTED: Table 2. Twitter corpus distribution by language label.
We begin by filtering the corpus to keep only those tweets where the user's self-declared language and the tweet's detected language correspond; that language becomes the tweet's correct language label. This operation cuts out roughly half the tweets, and leaves us with a corpus of about 900 million tweets in 54 different languages. Table TABREF6 shows the distribution of languages in that corpus. Unsurprisingly, it is a very imbalanced distribution of languages, with English and Japanese together accounting for 60% of all tweets. This is consistent with other studies and statistics of language use on Twitter, going as far back as 2013. It does however make it very difficult to use this corpus to train a LID system for other languages, especially for one of the dozens of seldom-used languages. This was our motivation for creating a balanced Twitter dataset.
FLOAT SELECTED: Table 2. Twitter corpus distribution by language label.
We begin by filtering the corpus to keep only those tweets where the user's self-declared language and the tweet's detected language correspond; that language becomes the tweet's correct language label. This operation cuts out roughly half the tweets, and leaves us with a corpus of about 900 million tweets in 54 different languages. Table TABREF6 shows the distribution of languages in that corpus.
Answer: EN, JA, ES, AR, PT, KO, TH, FR, TR, RU, IT, DE, PL, NL, EL, SV, FA, VI, FI, CS, UK, HI, DA, HU, NO, RO, SR, LV, BG, UR, TA, MR, BN, IN, KN, ET, SL, GU, CY, ZH, CKB, IS, LT, ML, SI, IW, NE, KM, MY, TL, KA, BO
Question: What classifiers did the authors use when doing the experiment?
Evidence: Disclaimer: Due to the nature of the paper, some examples contain highly offensive language and hate speech. They don't reflect the views of the authors in any way, and the point of the paper is to help fight such speech. Much recent interest has focused on the detection of offensive language and hate speech in online social media. Such language is often associated with undesirable online behaviors such as trolling, cyberbullying, online extremism, political polarization, and propaganda. Thus, offensive language detection is instrumental for a variety of application such as: quantifying polarization BIBREF0, BIBREF1, trolls and propaganda account detection BIBREF2, detecting the likelihood of hate crimes BIBREF3; and predicting conflict BIBREF4. In this paper, we describe our methodology for building a large dataset of Arabic offensive tweets. Given that roughly 1-2% of all Arabic tweets are offensive BIBREF5, targeted annotation is essential for efficiently building a large dataset. Since our methodology does not use a seed list of offensive words, it is not biased by topic, target, or dialect. Using our methodology, we tagged 10,000 Arabic tweet dataset for offensiveness, where offensive tweets account for roughly 19% of the tweets. Further, we labeled tweets as vulgar or hate speech. To date, this is the largest available dataset, which we plan to make publicly available along with annotation guidelines. We use this dataset to characterize Arabic offensive language to ascertain the topics, dialects, and users' gender that are most associated with the use of offensive language. Though we suspect that there are common features that span different languages and cultures, some characteristics of Arabic offensive language is language and culture specific. Thus, we conduct a thorough analysis of how Arabic users use offensive language. Next, we use the dataset to train strong Arabic offensive language classifiers using state-of-the-art representations and classification techniques. Specifically, we experiment with static and contextualized embeddings for representation along with a variety of classifiers such as a deep neural network classifier and Support Vector Machine (SVM).
The contributions of this paper are as follows:
We built the largest Arabic offensive language dataset to date that includes special tags for vulgar language and hate speech. We describe the methodology for building it along with annotation guidelines.
We performed thorough analysis of the dataset and described the peculiarities of Arabic offensive language.
We experimented with Support Vector Machine classifiers on character and word ngrams classification techniques to provide strong results on Arabic offensive language classification.
We experimented with Support Vector Machine classifiers on character and word ngrams classification techniques to provide strong results on Arabic offensive language classification.
Answer: Support Vector Machine classifiers
Question: What country most recently joined NATO?
Answer: Finland is the most recent country to join NATO, formally becoming a member on 4 April 2023. It is the 31st country to join the North Atlantic Treaty Organization.