DataHammer/scimrc huggingface dataset:
Question: What can I do to help me sleep better?
Answer: Make sure that you turn off your phone at least an hour before bedtime. Avoid eating close to bedtime. Make sure that you allow for enough time to spend in bed: at least 7-9 hours. Avoid drinking alcohol right before bed. Don't rely on substances to help you sleep. Get significant exercise during the day. For most people though, you don't want to exercise right before sleep. Avoid benzodiazepenes as much as possible because they have a significant tendency to lead to dependency and will interfere with sleep.
Question: Given a reference text about Pultenaea empetrifolia, tell me the colors of its flowers.
Evidence: Pultenaea empetrifolia is a species of flowering plant in the family Fabaceae and is endemic to the south-west of Western Australia. It is a spindly, prostrate or spreading shrub with down-curved, cylindrical, grooved leaves and yellow to orange and red flowers.

Description
Pultenaea empetrifolia is a spindly, prostrate or spreading shrub that typically grows to a height of up to 40 cm (16 in) and has glabrous stems. The leaves are cylindrical and curved strongly downwards with one or two grooves along the lower surface, 3–4.5 mm (0.12–0.18 in) long and 0.6–1.0 mm (0.024–0.039 in) wide with stipules at the base. The flowers are yellow to orange and red, and sessile or on a pedicel about up to 0.5 mm (0.020 in) long. The sepals are hairy and 4.0–4.6 mm (0.16–0.18 in) long with hairy bracteoles 1.5–3 mm (0.059–0.118 in) long at the base. The standard petal is 8.0–8.5 mm (0.31–0.33 in) long, the wings 7–8 mm (0.28–0.31 in) long and the keel 6.2–7.0 mm (0.24–0.28 in) long. Flowering occurs from September to October and the fruit is a pod.
Answer: The Pultenaea empetrifolia has yellow to orange and red flowers.
Question: Given the reference text about a towboat, how does the boat work?
Evidence: The boat measures 99 feet (30 m) long overall, with a hull length of 80 feet (24 m), and an 18-foot (5.5 m) beam. She draws 32 inches (0.8 m). She is powered by a 160-horsepower (120 kW) 1940 Fairbanks-Morse 35E10 direct reversing diesel engine. She measures 51 gross registry tons and displaces approximately 108 long tons (110 t). She is fashioned out of steel plates riveted to a steel frame. She has a scow-form bow fitted with special "knees" used in pushing barges, and a flat bottom with no keel
Answer: The boat is powered by a 160-horsepower 1940 Fairbanks-Morse 35E10 direct reversing diesel engine.
Question: Identify which car manufacturer is Chinese or American: Jeep, Karry
Answer: Karry is Chinese, Jeep is American
Question: Extract the names of Serbian political parties mentioned in the text and put them into a bulleted list.
Evidence: Serbia's electoral system was reformed in 2011, such that parliamentary mandates were awarded in numerical order to candidates on successful lists. Milisavljević received the forty-ninth position on the Democratic Party's Choice for a Better Life list and was re-elected when the list won sixty-seven mandates. The Serbian Progressive Party and the Socialist Party of Serbia formed a new coalition government after the election, and the Democratic Party moved into opposition. In 2013, Milisavljević proposed that the government of Serbia sell its high-powered Mercedes, Audi, and BMW cars in favour of the Fiat 500L model produced in Kragujevac. This proposal received some attention in the Italian media.
Answer: * Democratic Party
* Serbian Progressive Party
* Socialist Party of Serbia
Question: Did they experimnet in other languages?
Evidence: Moreover, our approach is also language independent. We have also performed preliminary experiments on the Arabic portion of the SemEval-2016 cQA task. The results are competitive with a hand-tuned strong baseline from SemEval-2015.
We have also performed preliminary experiments on the Arabic portion of the SemEval-2016 cQA task. 
Answer: Yes.
Question: What is WNGT 2019 shared task?
Evidence: The Transformer network BIBREF3 is a neural sequence-to-sequence model that has achieved state-of-the-art results in machine translation. However, Transformer models tend to be very large, typically consisting of hundreds of millions of parameters. As the number of parameters directly corresponds to secondary storage requirements and memory consumption during inference, using Transformer networks may be prohibitively expensive in scenarios with constrained resources. For the 2019 Workshop on Neural Generation of Text (WNGT) Efficiency shared task BIBREF0, the Notre Dame Natural Language Processing (NDNLP) group looked at a method of inducing sparsity in parameters called auto-sizing in order to reduce the number of parameters in the Transformer at the cost of a relatively minimal drop in performance.
For the 2019 Workshop on Neural Generation of Text (WNGT) Efficiency shared task BIBREF0, the Notre Dame Natural Language Processing (NDNLP) group looked at a method of inducing sparsity in parameters called auto-sizing in order to reduce the number of parameters in the Transformer at the cost of a relatively minimal drop in performance.
Answer: efficiency task aimed  at reducing the number of parameters while minimizing drop in performance
Question: What was Nicola Yoon's first published novel?
Answer: Everything, Everything, which was released in September 2015.
Question: Which of the following are men scientists: Marie Curie, Elizabeth Blackwell, Jane Goodall, Rosalind Franklin, Ada Lovelace, Maria Mitchell, Archimedes, Albert Einstein, Ernest Rutherford, Alfred Nobel, Alexander Fleming, Michael Faraday, Niels Bohr, Stephen Hawking, Alan Turing.
Answer: Archimedes, Albert Einstein, Ernest Rutherford, Alfred Nobel, Alexander Fleming, Michael Faraday, Niels Bohr, Stephen Hawking, Alan Turing are scientists who are men.
Question: Is Horsfieldia nervos a plant or animal?
Evidence: Horsfieldia nervosa is a species of plant in the family Myristicaceae. It is a tree endemic to Borneo where it is confined to Sarawak.
Answer: plant
Question: Given a reference text about the Davie School, tell me when it was added to the register of historic places and when it was open and closed..
Evidence: The Davie School (also known as the Old Davie School) is a historic school in Davie, Florida, USA. It is located at 6650 Griffin Road. It was designed by August Geiger. It opened its doors in 1918 to 90 students, and was in continuous use as a school until 1978. On March 29, 1988, it was added to the U.S. National Register of Historic Places. It is the oldest extant school building in Broward County.

School building
The architect Geiger was hired by the school board in 1917 and presented them with his plans for the school that September. It is a T-shaped two-story building constructed of concrete with a textured stucco finish. The building has a hip roof with a surrounding parapet. Architectural elements include horseshoe and bell-shaped openings, raised bands of stucco and multiple panel windows.
Answer: The Davie School opened in 1918 and closed in 1978. It was added to the U.S. National Register of Historic places on March 29, 1988.
Question: Write a short story about a little girl who befriends a dragon, the dragons magical powers can bring her to a different universe.
Answer: Once upon a time there was a little girl who dreamed every day of finding a dragon. This particular Tuesday morning when she was waiting for the bus, she spotted a shiny object on the sidewalk. She leaned down to pick it up and it glimmered in the sunshine. She had never seen such a brilliant treasure, it was the color of the rainbow, and when she looked closer it looked eerily similar to a dragon scale, but she couldn't believe that it was truly a dragon scale because they only existed in the stories she read. She looked around and spotted another shiny scale, like a trail of breadcrumbs leading her to the forest behind her house. She knew that her parents would want her to go to school but her curiosity got the better of her and she started to follow the trail of shiny scales to the forest. She fought her way through the forest until she came upon what looked like a cave that she was sure was not there before. She cautiously entered the cave and and instead of the cave getting darker, it was getting brighter, like a brilliant light was inside the cave. When she turned the corner in the cave, she saw the most beautiful sparkling dragon and could not believe her eyes! She slowly crept toward the dragon, who was watching her closely as she approached. She held out her hand as if to pet the dragon and the dragon sniffed her hand, then rubbed it's head on the bottom of her hand to signal that it wanted to befriend her. She giggled as the dragon purred and rubbed it's shiny body circling around her. The dragon then spoke and asked her if she had ever been to the beyond worlds. The girl shook her head, the dragon blinked her eyes and projected an image onto the cave wall to show one of the beautiful beyond worlds that was filled with dragons. The girl asked if the dragon would take her there, the dragon laughed and nodded, signaling for the girl to jump on it's back. The rush of excitement came over the girl, and she hopped on the dragons back. She held on tight as the dragon started running out of the cave, as the dragon exited the cave a portal opened and it leaped into the portal. The girl closed her eyes, not knowing what would happen next, she finally opened her eyes and gawked with amazement when they arrived in the beyond world, she could not believe what she was seeing, DRAGONS! DRAGONS EVERYWHERE! They were riding over the rainbow, playing in the waterfalls, and the universe was full of beautiful flowers towering as tall as redwood trees. The sky was purple and the world had 10 moons as she glanced up in the sky.......this was going to be a great adventure!
Question: Given a reference text about Larissa Ilinichna Volpert, tell me what game she played, when she was champion, and what titles she earned.
Evidence: Larissa Ilinichna Volpert (Russian: Лариса Ильинична Вольперт; 30 March 1926 – 1 October 2017) was a Soviet chess Woman Grandmaster and Russian and Estonian philologist. She was a three time Soviet women's chess champion (1954, 1958, and 1959).

Life
Born in Leningrad, she learned chess from her older brother and received chess instruction at the Leningrad Pioneers Palace. In 1947, she tied for first at the Leningrad Women's Championship. She played her first USSR Women's Championship in 1949 and finished equal fifth. In 1954, she won her first USSR Women's Championship. She scored 2–0 against Nina Hrušková-Bělská in the 1954 USSR v. Czechoslovakia match. In 1958 she shared the USSR Women's Championship title, and in 1959 she won for the third time, her second outright victory.

Volpert earned the Woman International Master title in 1954 and the Woman Grandmaster title in 1978. She had a degree in philology from Leningrad University and since 1977 taught Russian philology at the University of Tartu, Estonia. Her major works are about Pushkin's and Lermontov's poetry, especially in their connections to French literature. She died at the age of 91 on 1 October 2017.[3
Answer: Larissa Ilinichna Volpert played chess and was the Soviet women's chess champion in 1954, 1958 and 1959. She earned the titles of Woman International Master and Woman Grandmaster for her accomplishments in the game of chess.
Question: What's the objective of SNLI and MultiNLI datasets?
Evidence: We evaluate our method on natural language inference (NLI), paraphrase identification (PI), and sentiment classification. We also conduct analysis on gate values and experiments on model variants. For detailed experimental settings, we refer readers to the supplemental material.
For the NLI and PI tasks, there exists recent work specializing in sentence pair classification. However in this work we confine our model to the architecture that encodes each sentence using a shared encoder without any inter-sentence interaction, in order to focus on the effectiveness of the models in extracting semantics. But note that the applicability of CAS-LSTM is not limited to sentence encoding based approaches.
The objective of both datasets is to predict the relationship between a premise and a hypothesis sentence: entailment, contradiction, and neutral.
Answer: To predict the relationship bettheyen a premise and a hypothesis sentence: entailment, contradiction, and neutral.
Question: What are the benefits of working with a coach?
Answer: Working with a coach can help you move more quickly and effectively towards achieving your goals than if you worked alone. A coach can help you set the right goals, facilitate creating a plan of action to work towards your goals and help keep you accountable to taking the actions that will lead you towards achieving your goals.
Question: Is karaoke fun?
Answer: It depends.  Some people like karaoke, and some don't.  You might enjoy karaoke if, for example, you have an outgoing personality, like to sing or perform publicly, or enjoy bonding with others over music.  Others might find karaoke to be loud or may not like listening to amateur performers, who at times can also be intoxicated if performing at a karaoke bar.  In addition, when at a public location that offers karaoke, the songs are selected by the performer, so you cannot predict whether you will enjoy the music selection (unless you may happen to rent a private room where you can select all of the songs yourself, which is offered at certain karaoke institutions).  Interestingly, whether or not you personally would consider yourself to have a good voice does not always determine how much you will enjoy karaoke.
Question: Given this paragraph about Mahatma Gandhi, can you tell me why did he go to London?
Evidence: Gandhi had dropped out of the cheapest college he could afford in Bombay. Mavji Dave Joshiji, a Brahmin priest and family friend, advised Gandhi and his family that he should consider law studies in London. In July 1888, his wife Kasturba gave birth to their first surviving son, Harilal. His mother was not comfortable about Gandhi leaving his wife and family, and going so far from home. Gandhi's uncle Tulsidas also tried to dissuade his nephew. Gandhi wanted to go. To persuade his wife and mother, Gandhi made a vow in front of his mother that he would abstain from meat, alcohol and women. Gandhi's brother Laxmidas, who was already a lawyer, cheered Gandhi's London studies plan and offered to support him. Putlibai gave Gandhi her permission and blessing.

On 10 August 1888, Gandhi aged 18, left Porbandar for Mumbai, then known as Bombay. Upon arrival, he stayed with the local Modh Bania community whose elders warned him that England would tempt him to compromise his religion, and eat and drink in Western ways. Despite Gandhi informing them of his promise to his mother and her blessings, he was excommunicated from his caste. Gandhi ignored this, and on 4 September, he sailed from Bombay to London, with his brother seeing him off. Gandhi attended University College, London, where he took classes in English literature with Henry Morley in 1888–1889.

He also enrolled at Inner Temple with the intention of becoming a barrister. His childhood shyness and self-withdrawal had continued through his teens. He retained these traits when he arrived in London, but joined a public speaking practice group and overcame his shyness sufficiently to practise law
Answer: Gandhi travelled to London in the late 1880s to study law. He first took English literature classes and then enrolled in Inner Temple with the intention to become a barrister.
Question: Which is a species of fish? Tenpounder or Ninepounder
Answer: Tenpounder
Question: What is the problem with existing metrics that they are trying to address?
Evidence: Building Extractive CNN/Daily Mail
Building Extractive CNN/Daily Mail
Answer: Answer with content missing: (whole introduction) However, recent
studies observe the limits of ROUGE and find in
some cases, it fails to reach consensus with human.
judgment (Paulus et al., 2017; Schluter, 2017).
Question: Let me know if you think these are musical instruments or tools: Piano, chisel, Marimba, hammer, drill, scissor, violin, drums, screwdriver, brass, clarinet.
Answer: Piano, marimba, violin, drums and brass are all musical instruments. Piano belongs to the percussive chordophone family. A violin is a bowed stringed musical instrument. Marimba and the drums are percussion instruments. A brass falls under the category of wind instruments, while a clarinet is considered a woodwind instrument.

From your list, the following items are tools: chisel, hammer, drill and screwdriver. Chisel is a hand tool used for carving a hard material such as wood, stone, or metal. With a scissor, you normally cut paper and potentially some types of thin plastic. A hammer is a multi-purpose tool that you can use, for example, to secure objects with nails in wood, pull nails from wood and demolish objects. A drill is commonly used to drill holes or to drive screws into wood, metal, concrete and other materials. Last, a screwdriver is a mechanical hand tool that can you can use to drive screws in similar materials.
Question: Extract a list of all the administrative departments and function rooms found in the King's Building based on this paragraph.
Evidence: The King's Building is a Grade I listed building that forms part of the Strand Campus of King's College London in the United Kingdom. Originally named the College Building, the King's Building was designed by Sir Robert Smirke in the course of the College's foundation in 1829. As the founding building, it was built between 1829 and 1831 on land granted to King's College by the Government to complete the riverside frontage of Somerset House.

There are today a total of eight floors in the King's Building: Basement level, Ground level, Levels 1 to 4, Level 4U and Level 6. The King's Building houses a number of administrative departments (Estates & Facilities Offices, Admissions Office, Accommodation and Cashiers' Office), lecture theatres (most notably the Edmond J. Safra Lecture Theatre and Anatomy Lecture Theatre), the College Chapel, the Great Hall, various function rooms (Old Council Room, Committee Room, River Room, Somerset Room, St David's Room), study rooms and a catering outlet.
Answer: The administrative departments are Estates & Facilities Offices, Admissions Office, Accommodation and Cashiers' Office. The function rooms are Old Council Room, Committee Room, River Room, Somerset Room and St David's Room
Question: What languages do they experiment with?
Evidence: In order to train and evaluate open-domain factoid QA system for real-world questions, we build a new Chinese QA dataset named as WebQA. The dataset consists of tuples of (question, evidences, answer), which is similar to example in Figure FIGREF3 . All the questions, evidences and answers are collected from web. Table TABREF20 shows some statistics of the dataset.
In order to train and evaluate open-domain factoid QA system for real-world questions, we build a new Chinese QA dataset named as WebQA.
Answer: The answers are shown as follows:
* Chinese
Question: Why does the paper take free text into the study?
Evidence: Electronic Healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable content in a timely manner. Here we apply network-theoretical tools to the analysis of free text in Hospital Patient Incident reports in the English National Health Service, to find clusters of reports in an unsupervised manner and at different levels of resolution based directly on the free text descriptions contained within them. To do so, we combine recently developed deep neural network text-embedding methodologies based on paragraph vectors with multi-scale Markov Stability community detection applied to a similarity graph of documents obtained from sparsified text vector similarities. We showcase the approach with the analysis of incident reports submitted in Imperial College Healthcare NHS Trust, London. The multiscale community structure reveals levels of meaning with different resolution in the topics of the dataset, as shown by relevant descriptive terms extracted from the groups of records, as well as by comparing a posteriori against hand-coded categories assigned by healthcare personnel. Our content communities exhibit good correspondence with well-defined hand-coded categories, yet our results also provide further medical detail in certain areas as well as revealing complementary descriptors of incidents beyond the external classification. We also discuss how the method can be used to monitor reports over time and across different healthcare providers, and to detect emerging trends that fall outside of pre-existing categories.
Electronic Healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable content in a timely manner.
Answer: Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable content in a timely manner.
Question: What's the most popular tv show of all time in the USA?
Answer: Jeopardy!
Question: Should I pursue a degree after graduating high school?
Answer: Whether or not you pursue a degree after graduating high school is an important but complex question that depends on a variety of factors. When assessing what the right choice is for you, it is important to think about the career you'd like to pursue. If you enjoy classwork and can afford a college education, that is one route which may provide opportunities to earn a higher salary later in life. However, if you prefer being active and would like to begin earning money immediately after graduating high school without accumulating significant debt, forgoing an advanced degree to begin work can be a great option. At the end of the day, pursuing something that you enjoy spending time on is the most important aspect of this decision and will be a better indicator of both satisfaction and success than whether or not you earn an advanced degree.
Question: What is the show Parks and Rec about?
Answer: Parks and Rec is an American sitcom about the Parks and Recreation department of a small town in Indiana called Pawnee.
Question: How many components does the authors' model consist of?
Evidence: Since we focus on single-relation question answering in this work, our model decodes every question into a KB query that consists of exactly two elements–the topic entity, and the predicate. More formally, our model is a function $f(q, \lbrace e\rbrace , \lbrace p\rbrace )$ that takes as input a question $q$ , a set of candidate entities $\lbrace e\rbrace =e_1, ...,e_n$ , a set of candidate predicates $\lbrace p\rbrace =p_1,..., p_m$ , and produces a likelihood score $p(e_i, p_j|q)$ of generating entity $e_i$ and predicate $p_j$ given question $q$ for all $i\in {1...n}, j\in {1...m}$ .
As illustrated in Figure 1, our model consists of three components:
The details of each component are described in the following sections.
As illustrated in Figure 1, our model consists of three components:
Answer: Three.