DataHammer/scimrc huggingface dataset:
Question: If  you found yourself  washed  up on  a  deserted tropical island with no hope for immediate rescue, what  would  you do?
Answer: The immediate first step is to ensure you are not materially injured.  Assuming your only manifestation of harm is a psychological roller coaster of fear, anger and hopelessness,  your best course of action is to attend to your basic needs first.  

Locate a protected space away from the wind but not too deep into the surrounding jungle, built a fire pit and gather enough combustable materials to carry  you  through  the first few evenings.  Find fresh  water and someway to hold it (open coconut shells / fashioned palm leave bowls etc) - DO NOT DRINK IT until you boil it first over your new  fire so you mitigate the risk of getting sick.  Before your first nightfall with secure fire and water taken care of, build yourself a  make shift shelter so you  are protected from the elements and yet  to be discovered critters.  

Day two, focus your  energies  gathering food  (coconuts / seaweed / clams etc) so you keep your energy high.  Once your very basic needs are met (shelter / water / food to survive), its  time to fashion a fishing pole and a sharp spear out of bamboo so you can fish  and hunt for birds to expand your  food sources.  

Day  three, focus  your energy on building yourself a more permanent shelter.   Explore the island for  wood and rock sources; along with large palm leave you  can fashion rope from.  While exploring your  new home, look for caves and / or places  where you could construct a tree fort so you can improve your protected living space.

Week 2, once your new living  quarters are secured and you have sustainable methods to care for your basic needs, climb to the highest point of the island and look for nearby islands / land and any indication of human habitation.  While searching for these indicators, assess methods of island escape to get through any surf  and start tracking wind and weather patterns daily so you can get a feel for the seasonal rotations.

Week 3 +, dedicate 3-4 hours a day to building signal fires and SOS stone messages that overheard planes may be able to detect.  It is also important  to manage your mental health and track daily changes so you keep your sanity in check  as you adjust  to the new reality.

Create a way to chronicle your experiences.  One day you  will escape your island and can sell your story to Hollywood.  Of course, if you  never do escape, you will  at  least  have the comfort of leaving something behind for eventual discovery of proof you did survive the incident that landed you on this island.
Question: Which dataset(s) do they evaluate on?
Evidence: Traditional text-to-speech (TTS) systems are composed of complex pipelines BIBREF0 , these often include accoustic frontends, duration model, acoustic prediction model and vocoder models. The complexity of the TTS problem coupled with the requirement for deep domain expertise means these systems are often brittle in design and results in un-natural synthesized speech.
The open source LJSpeech Dataset was used to train our TTS model. This dataset contains around 13k <text,audio> pairs of a single female english speaker collect from across 7 different non-fictional books. The total training data time is around 21 hours of audio.
The architecture of our model utilizes RNN-based Seq2Seq model for generating mel spectrogram from text. The architecture is similar to that of Tacotron 2 BIBREF4 . The generated mel spetrogram can either be inverted via iterative algorithms such as Griffin Lim, or through more complicated neural vocoder networks such as a mel spectrogram conditioned Wavenet BIBREF11 .
Traditional text-to-speech (TTS) systems are composed of complex pipelines BIBREF0 , these often include accoustic frontends, duration model, acoustic prediction model and vocoder models
The open source LJSpeech Dataset was used to train our TTS model.
The architecture of our model utilizes RNN-based Seq2Seq model for generating mel spectrogram from text
Answer: The answers are shown as follows:
* LJSpeech
Question: What are popular street foods from Maharashtra in India
Answer: Some of the most popular street food list is Vada Pav, Misal Pav, Kanda Bhaji, Pav Bhaji , Sabudana Vada and Sabudana Khichadi. All of these are primarily vegetarian.
Question: Which family of moth does the Euxoa brevipennis belong to?
Evidence: Euxoa brevipennis is a moth of the family Noctuidae first described by Smith in 1888. In Canada, it is found in British Columbia, Alberta and Saskatchewan. In the United States, it has been recorded from Utah, Colorado and California.
Answer: The Euxoa brevipennis moth belongs to the Noctuidae family of moths.
Question: Why killing is sin?
Answer: Killing is sin because you can not kill human being.,
Question: How many manually annotated entities does the dataset contain?
Evidence: We describe a dataset developed for Named Entity Recognition in German federal court decisions. It consists of approx. 67,000 sentences with over 2 million tokens. The resource contains 54,000 manually annotated entities, mapped to 19 fine-grained semantic classes: person, judge, lawyer, country, city, street, landscape, organization, company, institution, court, brand, law, ordinance, European legal norm, regulation, contract, court decision, and legal literature. The legal documents were, furthermore, automatically annotated with more than 35,000 TimeML-based time expressions. The dataset, which is available under a CC-BY 4.0 license in the CoNNL-2002 format, was developed for training an NER service for German legal documents in the EU project Lynx.
The resource contains 54,000 manually annotated entities, mapped to 19 fine-grained semantic classes: person , judge , lawyer , country , city , street , landscape , organization , company , institution , court , brand , law , ordinance , European legal norm , regulation , contract , court decision, and legal literature.
Answer: 54000.
Question: How do you cook spare ribs on a pellet smoker?
Answer: Smoking ribs on a pellet smoker gives the meat a consistent, slow cook, helping to tenderize the meat. The best way to smoke ribs on a smoker consists of the 3-2-1 method. Cook on the grates for 3 hours at 225 degrees F with your choice of seasoning (don't forget to use mustard as a binder!), after 3 hours, double wrap the ribs in foil add & add butter wrap tight and place back on the smoker for 2 hours, for the last hour you will want to remove the tin foil and baste the ribs with your choice of BBQ sauce. Crank up the heat to 250 for the remaining hour. After the hour has been completed, take off and enjoy!
Question: Why do you like ballet so much?
Answer: Ballet is a true form of art. I enjoy taking ballet classes because we always dance with beautiful piano music during the floor and barre exercises. It is so relaxing when my body naturally dances with classical music. Ballet has some rigid rules when conducting certain movements, but it truly can be creative. Anyone at any age can attend a ballet class, and can create his or her own piece of ballet dance. 

Many people say Ballet is an intensive sport, because one often gets very sweaty after taking a ballet class. It is true that ballet is a good exercise for anyone who takes the class or performs on a stage. But because of the beautiful music that comes along during the classes, we/ballet dancers do not feel as tired as going to a gym or running a marathon. The music helps us forget about the soreness in muscles. Our bodies are as light as feathers during turns and leaps.
Question: What experiments they perform to demonstrate that their approach leads more accurate region based representations?
Evidence: The central problem we consider is category induction: given some instances of a category, predict which other individuals are likely to be instances of that category. When enough instances are given, standard approaches such as the Gaussian classifier from Section UNKREF9, or even a simple SVM classifier, can perform well on this task. For many categories, however, we only have access to a few instances, either because the considered ontology is highly incomplete or because the considered category only has few actual instances. The main research question which we want to analyze is whether (predicted) conceptual neighborhood can help to obtain better category induction models in such cases. In Section SECREF16, we first provide more details about the experimental setting that we followed. Section SECREF23 then discusses our main quantitative results. Finally, in Section SECREF26 we present a qualitative analysis.
As explained in Section SECREF3, we used BabelNet BIBREF29 as our reference taxonomy. BabelNet is a large-scale full-fledged taxonomy consisting of heterogeneous sources such as WordNet BIBREF36, Wikidata BIBREF37 and WiBi BIBREF38, making it suitable to test our hypothesis in a general setting.
BabelNet category selection. To test our proposed category induction model, we consider all BabelNet categories with fewer than 50 known instances. This is motivated by the view that conceptual neighborhood is mostly useful in cases where the number of known instances is small. For each of these categories, we split the set of known instances into 90% for training and 10% for testing. To tune the prior probability $\lambda _A$ for these categories, we hold out 10% from the training set as a validation set.
 In Section SECREF16, we first provide more details about the experimental setting that we followed. 
As explained in Section SECREF3, we used BabelNet BIBREF29 as our reference taxonomy. BabelNet is a large-scale full-fledged taxonomy consisting of heterogeneous sources such as WordNet BIBREF36, Wikidata BIBREF37 and WiBi BIBREF38, making it suitable to test our hypothesis in a general setting.
 To test our proposed category induction model, we consider all BabelNet categories with fewer than 50 known instances. This is motivated by the view that conceptual neighborhood is mostly useful in cases where the number of known instances is small. For each of these categories, we split the set of known instances into 90% for training and 10% for testing. To tune the prior probability $\lambda _A$ for these categories, we hold out 10% from the training set as a validation set.
Answer: The answers are shown as follows:
*  To test our proposed category induction model, we consider all BabelNet categories with fewer than 50 known instances. This is motivated by the view that conceptual neighborhood is mostly useful in cases where the number of known instances is small. For each of these categories, we split the set of known instances into 90% for training and 10% for testing.
Question: Do they report results only on English data?
Evidence: Dos and Don'ts for the Moral Choice Machine. The verb extraction identifies the most positive and most negative associated verbs in vocabulary, to infer socially desired and neglected behaviour. BIBREF0 (BIBREF0) extracted them with the general positive and negative association sets on the Google Slim embedding. Since those sets are expected to reflect social norms, they are referred as Dos and Don'ts hereafter.
Summarized, even though the contained positive verbs are quite diverse, all of them carry a positive attitude. Some of the verbs are related to celebration or travelling, others to love matters or physical closeness. All elements of the above set are rather of general and unspecific nature. Analogously, some of the negative words just describe inappropriate behaviour, like slur or misdeal, whereas others are real crimes as murder. As BIBREF0 (BIBREF0) describe, the listed words can be accepted as commonly agreed Dos and Don'ts.
Since those sets are expected to reflect social norms, they are referred as Dos and Don'ts hereafter.
Analogously, some of the negative words just describe inappropriate behaviour, like slur or misdeal, whereas others are real crimes as murder.
Answer: Yes.
Question: which marathon competition should I run?
Answer: The world marathon majors are the six most renowned and largest global marathon competitions. The six are: Tokyo Marathon (usually in March), Boston Marathon (usually in early Apr), London Marathon (usually in late Apr), Berlin Marathon (usually in Sep), Chicago Marathon (usually in Apr) and NYC Marathon (usually in Nov). For die-hard marathon runners, it is a dream come true to run all six. Meanwhile, some marathon events are famous for their breathtaking sceneries. For Rome Marathon, you run along cobblestone streets with sights of the Coliseum, St. Peter’s Square, and the Spanish Steps. The Great Wall Marathon in China is one of a kind race as runners climb the steep steps while enjoying the views rather than running on paved road. The Antarctica Marathon could be your most challenging and hard to reach marathon destination.The course is on King George Island. Runners run with penguins, seals and whales as their companions. The Big Sur Marathon in the US has its course on scenic Highway 1, the iconic Bixby Bridge marked the halfway point of the race, where runners can enjoy the unique site and a pianist performance!
Question: In the game of baseball, if a batter achieves three strikeouts in one game what is that called?
Answer: A Hat Trick - while in other sports the phrase is used for a positive sentiment like scoring three goals in soccer or hockey. Conversely, baseball's original definition comes with a negative connotation which is three strikeouts in one game.
Question: Who is Paulina Flores Arias
Answer: Paulina Flores Arias (born 1980 in Culiacán, Sinaloa) is a Mexican model, who after winning the national title of Nuestra Belleza México, represented her country in the 2000 Miss World pageant, held in London, England, on November 30, 2000. Paulina is currently a professional fashion model, and has been represented by several national and international modeling agencies.
Question: Does the new system utilize pre-extracted bounding boxes and/or features?
Evidence: In this section, we elaborate our model consisting of four parts: (a) image feature pre-selection part which models the tendency where people focus to ask questions, (b) question encoding part which encodes the question words as a condensed semantic embedding, (c) attention-based feature fusion part performs second selection on image features and (d) answer generation part which gives the answer output.
We propose to perform saliency-like pre-selection operation to alleviate the problems and model the RoI patterns. The image is first divided into $g\times g$ grids as illustrated in Figure. 2 . Taking $m\times m$ grids as a region, with $s$ grids as the stride, we obtain $n\times n$ regions, where $n=\left\lfloor \frac{g-m}{s}\right\rfloor +1$ . We then feed the regions to a pre-trained ResNet BIBREF24 deep convolutional neural network to produce $n\times n\times d_I$ -dimensional region features, where $d_I$ is the dimension of feature from the layer before the last fully-connected layer.
image feature pre-selection part which models the tendency where people focus to ask questions
We propose to perform saliency-like pre-selection operation to alleviate the problems and model the RoI patterns. The image is first divided into $g\times g$ grids as illustrated in Figure. 2 . Taking $m\times m$ grids as a region, with $s$ grids as the stride, we obtain $n\times n$ regions, where $n=\left\lfloor \frac{g-m}{s}\right\rfloor +1$ . We then feed the regions to a pre-trained ResNet BIBREF24 deep convolutional neural network to produce $n\times n\times d_I$ -dimensional region features, where $d_I$ is the dimension of feature from the layer before the last fully-connected layer.
Answer: Yes.
Question: Who would be your starting five on your current NBA team?
Answer: My starting five is not determined by who would be the best statistical performer at each position but more made up of which group of players I think would be the most fun to watch while also being a championship contender. To start, let's get the elephant out of the room, the big man down under has to be Joel Embiid for me. Offensively he is one of the best players in the league, no questions asked. Defensively, when he can stay out of foul trouble, he could easily make a run at DPOY (Defensive Player of the Year).  At the 4, im still going big because of this mans ability to move his feet. Jokic is a 280lb ballerina with Einstein'esque IQ and court vision like an owl. At the 3, I need a lock down defender and a court runner, oh, and two time MVP in Giannis Antetoukoumpo. I doubt this front court would be allowed to share an elevator. For my back court I need to support this tremendous front court cast with shooters and passers. Im going to pair Lamelo Ball with Luka Doncic to further bolster the teams height (avgs 6'9). Lamelo and Luka can both knock down the three ball, get to the paint off the dribble, execute the pick and roll flawlessly and are 6'6 and 6'7 respectively. This group should have no problem taking on any other 5 in the league and probably any historically.
Question: How many seasons is House the TV series?
Evidence: House (also called House, M.D.) is an American medical drama television series that originally ran on the Fox network for eight seasons, from November 16, 2004, to May 21, 2012. The series' main character is Dr. Gregory House (Hugh Laurie), an unconventional, misanthropic medical genius who, despite his dependence on pain medication, leads a team of diagnosticians at the fictional Princeton–Plainsboro Teaching Hospital (PPTH) in New Jersey. The series' premise originated with Paul Attanasio, while David Shore, who is credited as creator, was primarily responsible for the conception of the title character.
Answer: House, M.D. is an American medical drama television series that originally ran for eight seasons.
Question: Classify the below as food or drinks.
Fish, Meat, Salad, Apple, Lemonade, Coffee, Tea
Answer: Food - Fish, Meat, Salad, Apple
Drinks - Lemonade, Coffee, Tea
Question: Which of the following are US presidents and which are Hollywood actors: Jimmy Carter, George Washington, Denzel Washington, Daniel Day Lewis, Abraham Lincoln, and Ronald Reagan.
Answer: The presidents are: George Washington, Jimmy Carter, Abraham Lincoln, and Ronald Reagan. The Hollywood actors are: Daniel Day Lewis, Denzel Washington, and Ronald Reagan, who was an actor prior to becoming president.
Question: What did Stryk study at the Technical University of Munich?
Evidence: From 1984 to 1989 Stryk studied mathematics and computer science at the Technical University of Munich. In 1994 he received his doctorate in mathematics and then habilitated at the university. He was then postdoctoral researcher at TU Munich. Since 2000 he is professor of simulation, system optimization and robotics at the department of computer science of the Technische Universität Darmstadt. From April 2011 to March 2013 he was dean of the department. He was visiting professor and lecturer at the University of California, San Diego, and the Universidade Estadual de Campinas, Brazil. Stryk is vice president of Robocup. Since 2018 he has been building the German Rescue Robotics Centre.
Answer: Stryk studied mathematics and computer science at the Technical University of Munich.
Question: Different uses for glass
Answer: There are many but here are just a few. 
-Bulbs 
-Vases
-Windows
-Drinking glass
-Screens
-Plates
-Candles holder
-Water Bottles
-table top 
-French Door Glass
-Slippers (if you are a cinderella fan)
-Ash tray 
-coasters 
-Cooking pots
Question: When was the Roman empire founded?
Answer: The Roman empire was founded after the Republican period in 27BC and went through 1453AD. Some sources claim that the Roman Empire ended in 476AD with the fall of Rome via the Barbarian leader, Odoacer, however this is not true. The Roman empire continued on through the Eastern half of the Roman Empire. The Eastern Roman Empire is commonly referred to as the Byzantines. However, the Byzantines is a modern creation of referring to this Eastern Empire. In fact, all of the way through 1453AD, the people of the Eastern Roman Empire referred to themselves as Romans.
Question: What's the main benefits of a Subaru Forester Wilderness?
Evidence: Alongside the facelift model, Subaru released a new model called the Forester Wilderness for the North American market. It is intended to be a more off-road-oriented version of the Forester, and is positioned between the Limited and Touring trim levels in the Forester lineup. Visually, the Forester has more body cladding, and on the inside, copper-colored accents. It features a 0.5 inches (13 mm) lift for a total of 9.2 inches (230 mm) of ground clearance, the Wilderness also has all-terrain tires, a modified final drive ratio, and a stronger roof rack than previous models. Subaru's StarTex water-repellent seats are also standard.

The Wilderness is powered by the same 2.5-liter FB25D naturally-aspirated four cylinder engine powering other North American market Foresters. The Wilderness uses an Enhanced Dual-Function X-Mode version. The X-Mode is upgraded and re-tuned, with settings for snow, dirt, deep snow and mud. Additional wheel-slip is allowed to occur, which provides an advantage in harsh driving conditions.
Answer: The Forester Wilderness provides 0.5 inches (13 mm) lift that increases ground clearance to 9.2 inches (230mm). 
The vehicle comes with all-terrain tires, modified final drive ratio, stronger roof rack, and water-repellent seats. 
The engine size is the same, but it includes an enhanced dual-function x-mode with additional wheel-slip allowance to handle harsh driving conditions in snow, dirt, deep snow, and mud.
Question: Why is it important to vote?
Answer: Voting is a fundamental right and responsibility for citizens of any country. It helps citizens participate in democracy and influence key policies and decisions that influence everyone;s life
Question: Where did David Leatherbarrow receive his PhD from?
Evidence: David Leatherbarrow is Professor of Architecture and Chair of the Graduate Group in Architecture at the University of Pennsylvania School of Design, Philadelphia, where he has taught since 1984. He received his B.Arch. from the University of Kentucky and holds a Ph.D. in Art from the University of Essex. He has also taught in England, at Cambridge University and the University of Westminster (formerly the Polytechnic of Central London).
Answer: University of Essex
Question: From the paragraph provided, extract the recurring characters from Final Fantasy.  Separate them with a comma.
Evidence: The series features a number of recurring character archetypes. Most famously, every game since Final Fantasy II, including subsequent remakes of the original Final Fantasy, features a character named Cid. Cid's appearance, personality, goals, and role in the game (non-playable ally, party member, villain) vary dramatically. However, two characteristics many versions of Cid have in common are being a scientist or engineer, and being tied in some way to an airship the party eventually acquires. Every Cid has at least one of these two traits.

Biggs and Wedge, inspired by two Star Wars characters of the same name, appear in numerous games as minor characters, sometimes as comic relief. The later games in the series feature several males with effeminate characteristics. Recurring creatures include Chocobos, Moogles, and Cactuars. Chocobos are large, often flightless birds that appear in several installments as a means of long-distance travel for characters. Moogles are white, stout creatures resembling teddy bears with wings and a single antenna. They serve different roles in games including mail delivery, weaponsmiths, party members, and saving the game. Cactuars are anthropomorphic cacti with haniwa-like faces presented in a running or dashing pose. They usually appear as recurring enemy units, and also as summoned allies or friendly non-player characters in certain titles. Chocobo and Moogle appearances are often accompanied by specific musical themes that have been arranged differently for separate games
Answer: Cid, Biggs, Wedge, Chocobos, Moogles, Cactuars