DataHammer/scimrc huggingface dataset:
Question: Where are their datasets from?
Evidence: We collected datasets of news articles in English and German language from the news agency Reuters (Table TABREF13 ). After a data cleaning step, which was deleting meta information like author and editor name from the article, title, body and date were stored in a local database and imported to a Pandas data frame BIBREF12 . The English corpus has a dictionary of length 106.848, the German version has a dictionary of length 163.788.
For each article we extracted with the Python library “Spacy” the named entities labeled as person. “Spacy” was used because of its good performance BIBREF13 and it has pre-trained language models for English, German and others. The entity recognition is not perfect, so we have errors in the lists of persons. In a post processing step the terms from a list of common errors are removed. The names of the persons appear in different versions like “Donald Trump” or “Trump”. We map all names to the shorter version i.e. “Trump” in this example.
In Figure FIGREF15 you can see the time series of the mentions of “Trump” in the news, with a peak at the 8th of November 2016 the day of the election. It is also visible that the general level is changing with the election and is on higher level since then.
Taking a look at the histograms of the most frequent persons in some timespan shows the top 20 persons in the English news articles from 2016 to 2018 (Figure FIGREF16 ). As expected the histogram has a distribution that follows Zipfs law BIBREF14 , BIBREF15 .
From the corpus data a dictionary is built, where for each person the number of mentions of this person in the news per day is recorded. This time series data can be used to build a model that covers time as parameter for the relationship to other persons.
We collected datasets of news articles in English and German language from the news agency Reuters (Table 1).
Answer: The news agency Reuters.
Question: Which are the top 5 cities in population
Answer: 1/ Tokyo, Japan 2/Jakarta, Indonesia 3/Chongqing, China 4/Seoul, South Korea 5/Shanghai, China
Question: What kind of magazine was Nova
Evidence: Nova was a British glossy magazine that was published from March 1965 to October 1975 It was described by The Times as "a politically radical, beautifully designed, intellectual women's magazine." Nova covered such once-taboo subjects as abortion, cancer, the birth control pill, race, homosexuality, divorce and royal affairs. It featured stylish and provocative cover images.
Answer: Nova was a British glossy magazine that was published from March 1965 to October 1975.

It was described by The Times as "a politically radical, beautifully designed, intellectual women's magazine." 

Nova covered such once-taboo subjects as abortion, cancer, the birth control pill, race, homosexuality, divorce and royal affairs. It featured stylish and provocative cover images.
Question: Classify each of the following theme parks as Disney or Universal Studios: Magic Kingdom, Islands of Adventure, Epcot, Typhoon Lagoon, Volcano Bay
Answer: Magic Kingdom: Disney
Islands of Adventure: Universal Studios
Epcot: Disney
Typhoon Lagoon: Disney
Volcano Bay: Universal Studios
Question: What are some Australian craft beer brands that I should try?
Answer: Australia has many craft breweries that produce a variety of ales and lagers. You could try Balter beer, Black Hops or Green Beacon
Question: Classify the following into nouns and verbs : dog, run ,cat, John, eat, swim, Adam, fly
Answer: Nouns : dog, cat, John, Adam
Verbs : run, eat, swim, Fly
Question: What is the classification object of the paper?
Evidence: This study proposed the use of a transfer learning strategy based on fine-tuning to classify PD from speech in three different languages: Spanish, German, and Czech. The transfer learning among languages aimed to improve the accuracy when the models are initialized with utterances from a different language than the one used for the test set. Mel-scale spectrograms extracted from the transitions between voiced and unvoiced segments are used to train a CNN for each language. Then, the trained models are used to fine-tune a model to classify utterances in the remaining two languages.
The results indicate that the transfer learning among languages improved the accuracy of the models in up to 8% when a base model trained with Spanish utterances is used to fine-tune a model to classify PD German utterances. The results obtained after the transfer learning are also more balanced in terms of specificity-sensitivity and have a lower variance. In addition, the transfer learning among languages scheme was accurate to improve the accuracy in the target language only when the base model was robust enough. This was observed when the model trained with Spanish utterances was used to initialize the models for German and Czech languages.
Further experiments will include the development of more robust base models using hyper-parameter optimization strategies like those based on Bayesian optimization. In addition, the base models will be trained considering two of the languages instead of only one of them. The trained models will also be evaluated to classify the speech of PD patients in several stages of the disease based on the MDS-UPDRS-III score, or based on their dysarthria severity BIBREF20. Further experiments will also include transfer learning among diseases, for instance training a base model with utterances to classify PD, and use such a model to initialize another one to classify other neurological diseases such as Hungtinton's disease.
This study proposed the use of a transfer learning strategy based on fine-tuning to classify PD from speech in three different languages: Spanish, German, and Czech.
Answer: Parkinson's disease.
Question: How to make a cup of yummy chai?
Answer: Boil a cup of water, add a slice of ginger and some mint leaves. After a few minutes, add a table spoon of tea leaves and then finally add milk and sugar per taste. Boil for two minutes. Finally, filter the chai using a strainer. Voila!
Question: What are some movies that star Will Ferrell?
Answer: Some of the most popular movies starring Will Ferrell include Old School, Stepbrothers, Elf, Anchorman, Stranger than Fiction, Blades of Glory, Zoolander, and Talladega Nights: The Ballad of Ricky Bobby.
Question: Clarence Albert Pierce, Jr., tell me where he was born and what college he went attended.
Evidence: Clarence Albert Pierce, Jr. (born October 1, 1928) is an American politician in the state of Mississippi. He served in the Mississippi House of Representatives from 1952 to 1984. He was a teacher and farmer. He attended the University of Mississippi, graduating in 1950. Pierce served as an assistant to Senator James Eastland when the Mississippi House was not in session.
Answer: Clarence Albert Pierce, Jr. was born on October 1, 1928 and attended the University of Mississippi.
Question: Can you give me 6 popular types of pets?
Answer: Dogs, Cats, Fish, Birds, Chickens and Horses
Question: What improvement does the MOE model make over the SOTA on language modelling?
Evidence: The two models achieved test perplexity of INLINEFORM0 and INLINEFORM1 respectively, showing that even in the presence of a large MoE, more computation is still useful. Results are reported at the bottom of Table TABREF76 . The larger of the two models has a similar computational budget to the best published model from the literature, and training times are similar. Comparing after 10 epochs, our model has a lower test perplexity by INLINEFORM2 .
In addition to the largest model from the previous section, we trained two more MoE models with similarly high capacity (4 billion parameters), but higher computation budgets. These models had larger LSTMs, and fewer but larger and experts. Details can be found in Appendix UID77 . Results of these three models form the bottom line of Figure FIGREF32 -right. Table TABREF33 compares the results of these models to the best previously-published result on this dataset . Even the fastest of these models beats the best published result (when controlling for the number of training epochs), despite requiring only 6% of the computation.
FLOAT SELECTED: Table 1: Summary of high-capacity MoE-augmented models with varying computational budgets, vs. best previously published results (Jozefowicz et al., 2016). Details in Appendix C.
The two models achieved test perplexity of INLINEFORM0 and INLINEFORM1 respectively, showing that even in the presence of a large MoE, more computation is still useful. Results are reported at the bottom of Table TABREF76 . The larger of the two models has a similar computational budget to the best published model from the literature, and training times are similar. Comparing after 10 epochs, our model has a lower test perplexity by INLINEFORM2 .
 Table TABREF33 compares the results of these models to the best previously-published result on this dataset . Even the fastest of these models beats the best published result (when controlling for the number of training epochs), despite requiring only 6% of the computation.
FLOAT SELECTED: Table 1: Summary of high-capacity MoE-augmented models with varying computational budgets, vs. best previously published results (Jozefowicz et al., 2016). Details in Appendix C.
Answer: Perpexity is improved from 34.7 to 28.0.
Question: Who is the haas formula 1 team principal?
Answer: The current team principal of the Moneygram Haas F1 team is Geunther Steiner
Question: I need some ideas for a first date.
Answer: -  Dinner at your favorite pizzeria 
- A walk around a local park
- Mid-afternoon coffee at a local coffee shop
- Tour a museum
Question: Categorize the following list into common greetings and common parting words: goodbye, hi, hiya, howdy, see ya, what's up, i'm out, how are you, how are you doing, peace, sup, talk to you later, see you soon, have a good one
Answer: Common greetings: hi, hiya, howdy, what's up, how are you, how are you doing, sup
Common parting words: goodbye, see ya, i'm out, peace, talk to you later, see you soon, have a good one
Question: Is it better to live in the city or the suburbs?
Answer: I enjoyed living in the city when I was younger and spent a lot of time with friends; it was very convenient to be close to everyone. As I got older and had kids, it was important to have more space in my home - I was spending more time inside my home than outside it. When I retire, I may want to go back in to the city.
Question: "The Day the Music Died" refers to the tragic deaths of which artists?
Answer: Buddy Holly, Ritchie Valens and The Big Bopper
Question: What are the pros and cons of outdoor and indoor soccer?
Answer: Outdoor soccer is more appealing as we are out in nature. 
The outdoor field is bigger
Outdoor soccer is most popular
Major soccer tournaments worldwide are played outdoors, including the World Cup

Indoor soccer is good to play when the weather outside is bad
Indoor soccer often results in way more touches on the ball for a player. 
Indoor soccer has some unique strategies that can make the sport more interesting. 
Indoor soccer tends to have more goals scored and hence more entertainment.
Question: What year was the first pizzeria in New York founded?
Answer: Lombardi's Pizzeria in Little Italy in New York City claims to be the oldest NYC pizzeria and was opened in 1905.
Question: What are some good date ideas?
Answer: Tour an animal rescue, dine at a local vegan restaurant, visit the art museum, explore a botanical garden, plant-based picnic in the park, volunteer at a humane society to walk the dogs or play with the cats, hike at a local state or national park
Question: What's the best for indoor plant?
Answer: 1. Give less water only as much needed, do not over water it
2. Keep it in indirect sunlight at least for 2 hours a day
Question: Please important statistics from this passage.
Evidence: India's nominal per capita income was US$1,670 per year in 2016, ranked 112th out of 164 countries by the World Bank, while its per capita income on purchasing power parity (PPP) basis was US$5,350, and ranked 106th. Other estimates for per capita gross national income and gross domestic product vary by source. For example, India's average GDP per capita on PPP basis in 2009, according to The Economist, was US$5,138, with significant variation among its states and union territories. Goa had the highest per capita PPP GDP at US$14,903, while Bihar the lowest with per capita PPP GDP of US$682 as of 2015 In rupee terms, India's per capita income grew by 10.4% to reach Rs.74,920 in 2013-
Answer: 1. India's nominal  Per capita income was US$1,670 per year in 2016
 2. India's rank on per capita Income was 112 out of 164
 3. India's per capita income on purchasing power parity (PPP) basis was US$5,350
 4.India's rank based on purchasing power parity was 106th
 5.India's average GDP per capita on PPP basis in 2009 was US$5,138
 6. Goa had the highest per capita PPP GDP at US$14,903
 7. Bihar the lowest with per capita PPP GDP of US$682
 8.India's per capita income grew by 10.4% to reach Rs.74,920
Question: What is the JDK?
Answer: The JDK is a development environment for building applications using the Java programming language. The JDK includes tools useful for developing and testing programs written in the Java programming language and running on the Java platform.
Question: Does the dataset only involve one language?
Evidence: We extract a large-scale stance detection dataset from comments written by candidates of elections in Switzerland. The dataset consists of German, French and Italian text, allowing for a cross-lingual evaluation of stance detection. It contains 67 000 comments on more than 150 political issues (targets). Unlike stance detection models that have specific target issues, we use the dataset to train a single model on all the issues. To make learning across targets possible, we prepend to each instance a natural question that represents the target (e.g."Do you support X?"). Baseline results from multilingual BERT show that zero-shot cross-lingual and cross-target transfer of stance detection is moderately successful with this approach.
The dataset consists of German, French and Italian text, allowing for a cross-lingual evaluation of stance detection.
Answer: No.
Question: Who is the Ferrari formula 1 team principal?
Answer: The Scuderia Ferrari Team Principal is Fred Vasseur
Question: What is the “infield” in baseball?
Answer: The infield is the area of a baseball field that extends from home base out past first, second and third bases. The infield is usually a dirt surface, and the outfield begins where the dirt turns to grass.
Question: What is the smallest bird?
Evidence: Hummingbirds have varied specialized characteristics to enable rapid, maneuverable flight, exceptional metabolic capacity, adaptations to high altitude, sensitive visual and communication abilities, and long-distance migration in some species. Among all birds, male hummingbirds have the widest diversity of plumage color, particularly in blues, greens, and purples. Hummingbirds are the smallest mature birds, measuring 7.5–13 cm (3–5 in) in length. The smallest is the 5 cm (2.0 in) bee hummingbird, which weighs less than 2.0 g (0.07 oz), and the largest is the 23 cm (9.1 in) giant hummingbird, weighing 18–24 grams (0.63–0.85 oz). Noted for long beaks, hummingbirds are specialized for feeding on flower nectar, but all species also consume small insects.
Answer: Hummingbird is the smallest bird.
Question: Why is ice hockey a good sport for women?
Answer: Ice Hockey is common sport for women, which is most popular in New England, the Midwest, and Canadian. Ice Hockey promotes confidence, agility, speed and  team work,  Many programs are available for young children as part of a learn-to-skate, co-ed and all-gender programs.  Strong relationships are developed amongst teammates as they develop a common goal to develop skill and perform in games.
Question: Give me a history of Valve
Evidence: Founding and Half-Life (1996–2003)

Gabe Newell (foreground) and Doug Lombardi (background), 2007
Valve was founded as Valve, LLC, in 1996 by former Microsoft employees Gabe Newell and Mike Harrington. Newell had spent the prior 13 years at Microsoft developing Windows, including the Windows 95 port of Doom. Wanting to move onto a new venture using their shared wealth, Newell and Harrington founded Valve, L.L.C. in Kirkland, Washington (about five miles from the Microsoft campus in Redmond), on August 24, 1996, Newell's wedding day. Alternative names considered by Newell and Harrington include Fruitfly Ensemble and Rhino Scar.

Valve's first game was Half-Life, a first-person shooter (FPS) with elements of horror. The development was aided by access to the Quake engine by id Software; Valve modified this engine into their GoldSrc engine. After struggling to find a publisher, Valve eventually signed with Sierra On-Line. Half-Life was released in November 1998 and was a critical and commercial success. With its realism, scripted sequences and seamless narrative, it had a lasting influence; according to IGN in 2014, the history of the FPS genre "breaks down pretty cleanly into pre-Half-Life and post-Half-Life eras".
Answer: Founding and Half-Life (1996–2003): Valve was founded as Valve, LLC, in 1996 by former Microsoft employees Gabe Newell and Mike Harrington in Kirkland, Washington. Valve's first game is Half-Life, a first-person shooter (FPS) released in November 1998. It was developed using the modified Quake engine GoldSrc. After struggling to find a publisher, Valve eventually signed with Sierra On-Line.
Question: What are some of the best vegan protein sources?
Answer: Soy-based products such as tofu, soy milk and tempeh are high sources of protein. Pulses such as beans (including chickpeas, pintos, black beans) and lentils. Certain grains are also high-protein sources, such as quinoa, farro and buckwheat. Other foods like nuts and seeds are good protein sources but are also high in fat and calories.
Question: Write me a script for an upcoming All Hands meeting about our IPO prospects and how employees need to act in the quiet period.
Answer: Lately, I've received plenty of questions about a potential IPO. I want to answer those questions today — and talk about how we as a company will answer questions like that moving forward.

For years, we’ve shared that one of our aspirations is to build a wildly successful public company. Everyone has a role to play in getting us there and delivering for customers and growing the business is the most important thing most of us can do.

A typical milestone on a high-growth journey is an IPO. But as companies get more serious about a potential IPO, there is a period where they stop talking about an IPO.  This might be counter-intuitive, but here’s why: there are important regulatory restrictions on what companies can and cannot say when it comes to company growth and plans as they approach becoming a public company. The consequences if you don’t follow those rules can be serious — the SEC can even delay our ability to go public if it determines we’ve improperly promoted an IPO. And that’s obviously a situation we want to avoid, should we be in a position to go public in the future.  

And even language like this — "should we be in a position to go public in the future" — is vague. That's for a reason: as we get closer to an IPO, what we can say is restricted and we need to make sure we don’t make promises, otherwise regulators could force us to delay our plans.

So I’m going to share some updates about how we’ll need to communicate related to a potential IPO:

In order to preserve the ability to IPO at some point in the future, the executive team and I will not be sharing explicit details on our IPO journey or timing at All Hands or in other company communications. We also won’t be sharing updates to our market valuation. 

Hiring managers and recruiters should not explicitly talk about an IPO or our revenue growth with candidates. Instead, emphasize our massive opportunity, how we’re innovating, delivering value to our customers, and what an awesome team we have.  

We can’t engage with public market investors or financial journalists on certain topics. That means if a financial analyst, research analyst or reporter reaches out to you, don’t respond and forward the email to the communications team.

We also can’t talk about a potential IPO on social media or with friends and family. You get the idea.

I know that this will be different for us. We’ve always been a transparent company and this change is hopefully a short-term one. But it is an important one and you all have a role to play in helping us remain compliant.

We all have different, important roles to play in making this company a successful, long-term business. The most important thing we can all do is to continue delivering for our customers and building a successful business.
Question: Write an email to a butcher asking how much and what types of meats would be best for a BBQ for 20 people. And ask for a quote.
Answer: Hi <name of Butcher>, I need to organise a meat order for an upcoming BBQ for 20 people. Could you please suggest some cuts of meat and some quantities for that number of people. Could I also please get a quote for the total quantity. Kind regards, <name>.
Question: Tell me whether these are countries or continents
Answer: Africa, Asia, Spain, Vietnam, China, Europe, North America
Question: Which companies did Theranos partner with in 2015?
Evidence: In 2012 Safeway invested $350 million into retrofitting 800 locations with clinics that would offer in-store blood tests. After many missed deadlines and questionable results from a trial clinic at Safeway's corporate offices, the deal was terminated in 2015. In 2013, Theranos partnered with Walgreens to offer in-store blood tests at more than 40 locations. Although Theranos blood tests were reportedly used on drug trial patients for GlaxoSmithKline and Pfizer, both companies stated that there were no active projects with Theranos in October 2015. In June 2016, Walgreens terminated its partnership with Theranos. In November 2016 it filed suit against Theranos in federal court in Delaware for breach of contract. In June 2017, Theranos reported to investors that the suit, which originally sought $140 million in damages, was settled for less than $30 million.

In March 2015 the Cleveland Clinic announced a partnership with Theranos to test its technology and decrease the cost of lab tests. In July 2015, Theranos became the lab-work provider for Pennsylvania insurers AmeriHealth Caritas and Capital Blue Cross.

In July 2015 the Food and Drug Administration approved the use of the company's fingerstick blood testing device for the herpes simplex virus (HSV-1) outside a clinical laboratory setting. Theranos was named the 2015 Bioscience Company of the Year by the Arizona BioIndustry Association (AzBio).
Answer: Theranos partnered with Cleveland Clinic in March 2015 to test its technology and decrease the cost of lab tests. In July 2015, Theranos became the lab-work provider for Pennsylvania insurers AmeriHealth Caritas and Capital Blue Cross.
Question: Who was Edward Gramlich
Evidence: Edward M. Gramlich (June 18, 1939 – September 5, 2007) was an American economist who served as a member of the Federal Reserve Board of Governors from 1997 to 2005. Gramlich was also an acting director of the Congressional Budget Office.

Gramlich graduated from Williams College in 1961 and received a master's degree in 1962 and a Ph.D. in economics in 1965 from Yale University. He joined the Federal Reserve as a research economist from 1965 to 1970, and was a senior fellow at the Brookings Institution from 1973 to 1976. He then taught economics and public policy at the University of Michigan from 1976 to 1997, including a term as dean of the Gerald R. Ford School of Public Policy, and returned to Michigan as a professor in 2005.
Answer: Edward M. Gramlich (June 18, 1939 – September 5, 2007) was an American economist who served as a member of the Federal Reserve Board of Governors from 1997 to 2005. Gramlich was also an acting director of the Congressional Budget Office.