DataHammer/scimrc huggingface dataset:
Question: How to make a Pizza dough?
Answer: Combine about 1 cup (125g) of white flour, yeast, granulated sugar, and kosher salt in a big bowl. You may add garlic powder and dried basil powder as well. Add virgin olive oil and warm water and stir thoroughly. Gradually add another cup of white flour and keep stirring until the dough is shaped into a ball and doesn't stick to the bowl.
Question: In the series A Song of Ice and Fire, who is the founder of House Karstark?
Answer: Karlon Stark
Question: What is a bunk bed?
Answer: It’s a type of furniture that stacks two or more beds on top of each other. Bunk beds are typically used in children’s rooms and in places where it’s necessary to fit lots of beds in a small amount of space.
Question: What are the two challenges in evaluating the implications of news?
Evidence: In this section we outline the evaluation plan to verify the effectiveness of our learning approaches. To evaluate the news suggestion problem we are faced with two challenges.
What comprises the ground truth for such a task ?
How do we construct training and test splits given that entity pages consists of text added at different points in time ?
Consider the ground truth challenge. Evaluating if an arbitrary news article should be included in Wikipedia is both subjective and difficult for a human if she is not an expert. An invasive approach, which was proposed by Barzilay and Sauper BIBREF8 , adds content directly to Wikipedia and expects the editors or other users to redact irrelevant content over a period of time. The limitations of such an evaluation technique is that content added to long-tail entities might not be evaluated by informed users or editors in the experiment time frame. It is hard to estimate how much time the added content should be left on the entity page. A more non-invasive approach could involve crowdsourcing of entity and news article pairs in an IR style relevance assessment setup. The problem of such an approach is again finding knowledgeable users or experts for long-tail entities. Thus the notion of relevance of a news recommendation is challenging to evaluate in a crowd setup.
We take a slightly different approach by making an assumption that the news articles already present in Wikipedia entity pages are relevant. To this extent, we extract a dataset comprising of all news articles referenced in entity pages (details in Section SECREF40 ). At the expense of not evaluating the space comprising of news articles absent in Wikipedia, we succeed in (i) avoiding restrictive assumptions about the quality of human judgments, (ii) being invasive and polluting Wikipedia, and (iii) deriving a reusable test bed for quicker experimentation.
The second challenge of construction of training and test set separation is slightly easier and is addressed in Section SECREF46 .
To evaluate the news suggestion problem we are faced with two challenges. • What comprises the ground truth for such a task ? • How do we construct training and test splits given that entity pages consists of text added at different points in time ?
Answer: • What comprises the ground truth for such a task ? • How do they construct training and test splits given that entity pages consists of text added at different points in time ?
Question: Why did people stop using Perl?
Answer: Perl was declared death because the new Perl6, in development since 2000, wasn't there yet to get into production modes. Perl was seen as the old language without any future.
Question: From the passage provided, extract the progression of number of games in an NFL season.
Evidence: From 1920 to 1934, the NFL did not have a set number of games for teams to play, instead setting a minimum. The league mandated a twelve-game regular season for each team beginning in 1935, later shortening this to eleven games in 1937 and ten games in 1943, mainly due to World War II. After the war ended, the number of games returned to eleven games in 1946, and later back to twelve in 1947. The NFL went to a 14-game schedule in 1961, which it retained until switching to a 16-game schedule in 1978. In March 2021, the NFL officially adopted a 17-game schedule after gaining the agreement of the National Football League Players Association (NFLPA).
Answer: In the early years of the NFL the league simply mandated a minimum of 12 games played each season from 1920-1934. In 1937 teams played 11 games. In 1943 teams played 10 games due to World War II. By 1947 teams were playing 12 games per season. From 1961 to 1978 teams played 14 games per season before playing 16 games per season until 2021. Each NFL team plays 17 games per season in present day.
Question: What type of movie is Nope?
Answer: Nope is a science-fiction horror movie released in 2022.
Question: Is infinite-length sequence generation a result of training with maximum likelihood?
Evidence: We extended the notion of consistency of a recurrent language model put forward by BIBREF16 to incorporate a decoding algorithm, and used it to analyze the discrepancy between a model and the distribution induced by a decoding algorithm. We proved that incomplete decoding is inconsistent, and proposed two methods to prevent this: consistent decoding and the self-terminating recurrent language model. Using a sequence completion task, we confirmed that empirical inconsistency occurs in practice, and that each method prevents inconsistency while maintaining the quality of generated sequences. We suspect the absence of decoding in maximum likelihood estimation as a cause behind this inconsistency, and suggest investigating sequence-level learning as an alternative in the future.
Inconsistency may arise from the lack of decoding in solving this optimization problem. Maximum likelihood learning fits the model $p_{\theta }$ using the data distribution, whereas a decoded sequence from the trained model follows the distribution $q_{\mathcal {F}}$ induced by a decoding algorithm. Based on this discrepancy, we make a strong conjecture: we cannot be guaranteed to obtain a good consistent sequence generator using maximum likelihood learning and greedy decoding. Sequence-level learning, however, uses a decoding algorithm during training BIBREF25, BIBREF26. We hypothesize that sequence-level learning can result in a good sequence generator that is consistent with respect to incomplete decoding.
We suspect the absence of decoding in maximum likelihood estimation as a cause behind this inconsistency, and suggest investigating sequence-level learning as an alternative in the future.
Inconsistency may arise from the lack of decoding in solving this optimization problem. Maximum likelihood learning fits the model $p_{\theta }$ using the data distribution, whereas a decoded sequence from the trained model follows the distribution $q_{\mathcal {F}}$ induced by a decoding algorithm. Based on this discrepancy, we make a strong conjecture: we cannot be guaranteed to obtain a good consistent sequence generator using maximum likelihood learning and greedy decoding.
Answer: There are is a strong conjecture that it might be the reason but it is not proven.
Question: Name a few cities worldwide where traffic congestion is an issue
Answer: Los Angeles, Mumbai, Manila, Jakarta, Bangkok, Sao Paulo
Question: I'm creating a class to explain to kids the difference between items that are powered and can be plugged in and items that aren't. Please divide the following things into those you can plug in and those that you can't: table, hairdryer, television, chair, computer, fridge, comb, flowers.
Answer: A hairdryer, television, computer and fridge are all examples of things that can be plugged in and powered by electricity. A common table, chair, comb and flower are examples of items that do not require electricity and cannot be plugged in.
Question: Write a motivating note to a friend who wants to lose weight
Answer: There are three parts to achieving any goal you set for yourself:
1. Vision : Visualize your ideal end goal (lose 25 pounds!) 
2. Action : Set up a daily plan of action (walk every day for 60 minutes, give up ice cream) 
3. Celebration : Plan an amazing celebration when you reach your goal (and yes, with ice cream!)
Question: What two types the Chinese reading comprehension dataset consists of?
Evidence: Cloze Track: In this track, the participants are required to use the large-scale training data to train their cloze system and evaluate on the cloze evaluation track, where training and test set are exactly the same type.
User Query Track: This track is designed for using transfer learning or domain adaptation to minimize the gap between cloze training data and user query evaluation data, i.e. training and testing is fairly different.
Cloze Track
User Query Track
Answer: cloze-style reading comprehension and user query reading comprehension questions
Question: Tell me whether these dog breeds need lots of exercise: Golden Retriever, German Shepherd, Springer, Husky, French Bulldog, Pekingese, Pomeranian, Chihuahua
Answer: Golden Retriever and German Shepherd need daily constant exercise, at least twice a day. Springers needs lots of exercise as well, preferred 2 hours per day. Similarly for Husky.

On the other hand, French Bulldog's need on exercise is minimal and owners should avoid high intensity exercise for French Bulldog. Similarly for Pekingese, as they have shorter nose, so owners should not overdo the exercise otherwise Pekingese will struggle. Owners should also avoid overdoing exercise for Pomeranian. 

Chihuahua doesn't need as much exercise as retrievers or Shepherds, but it still need certain level of exercise to keep active. 

It's the best to consult your vet per your dog's condition.
Question: Where is Black Oak?
Evidence: Black Oak is a community in White River Township, Washington County, Arkansas, United States. It is located between Greenland and Elkins and lies six miles southeast of Fayetteville.

The community lies along the west bank of the Middle Fork of the White River. The community of Sulphur City lies on the east bank of the river approximately 1.5 mile to the southeast.
Answer: Black Oak is a community is Arkansas, United States.
Question: Is it safe for dogs to eat grapes?
Answer: No, grapes are considered dangerous for dogs to consume.
Question: What phenomena prevent models from learning good translations?
Evidence: Although most UTD matches are across speakers, recall of cross-speaker matches is lower than for same-speaker matches. As a result, the same word from different speakers often appears in multiple clusters, preventing the model from learning good translations. ZRTools discovers 15,089 clusters in our data, though there are only 10,674 word types. Only 1,614 of the clusters map one-to-one to a unique word type, while a many-to-one mapping of the rest covers only 1,819 gold types (leaving 7,241 gold types with no corresponding cluster).
Fragmentation of words across clusters renders pseudoterms impossible to translate when they appear only in test and not in training. Table TABREF10 shows that these pseudotext out-of-vocabulary (OOV) words are frequent, especially in the call-level split. This reflects differences in acoustic patterns of different speakers, but also in their vocabulary — even the oracle OOV rate is higher in the call-level split.
As a result, the same word from different speakers often appears in multiple clusters, preventing the model from learning good translations.
Answer: As a result, the same word from different speakers often appears in multiple clusters, preventing the model from learning good translations.
Question: Is the USS Rachel Seaman made of metal?
Evidence: USS Rachel Seaman was a wooden schooner purchased by the Union Navy during the American Civil War.
Answer: No, it is made of wood.
Question: Given this paragraph about the dimensions of a volleyball court, what is the area of one half of a volleyball court with an explanation of the math behind the calculation.
Evidence: A volleyball court is 9 m × 18 m (29.5 ft × 59.1 ft), divided into equal square halves by a net with a width of one meter (39.4 in). The top of the net is 2.43 m (7 ft 11+11⁄16 in) above the centre of the court for men's competition, and 2.24 m (7 ft 4+3⁄16 in) for women's competition, varied for veterans and junior competitions.
Answer: The area of one half of a volleyball court is 81 square meters. The total area of the court is 162 square meters (9 m x 18 m). It is divided into two equal square halves of 81 square meters each (9 m x 9 m).
Question: what are the five pillars of migration or modernization from a legacy data warehouse to a modern lakehouse?
Answer: 1. Architecture/infrastructure: Establish the deployment
architecture and implement a security and governance
framework.
2. Data migration: Map data structures and layout, complete a
one-time load, and finalize an incremental load approach.
3.ETL and pipelines: Migrate data transformation and
pipeline code, orchestration, and jobs in this phase. Speed
up your migration by using automation tools and comparing
your results with on-premises data and expected results.
4. Analytics: Repoint reports and analytics for business
analytics and business outcomes. Reporting semantic layers
and online analytics processing (OLAP) cubes should also
repoint to the lakehouse via Open Database Connectivity
(ODBC) and Java Database Connectivity (JDBC).
5. Data science/machine learning (ML): Establish connectivity
to ML tools and onboard data science teams.
Question: How do I become successful?
Answer: Success is not a measure of wealth or assets as many people come to believe. And giving someone advice on how to be success can be very tricky as each person has such a diverse background, experiences, ability, strengths, weaknesses, networks, and everything else in between. Therefore a framework of thought is the best way to consider success. To be successful, you must find what you're best at and put yourself in an environment that allows you to do what you're best at.
Question: Give me a bulleted list of the distinctive physical characteristics of Beavers described in this passage.
Evidence: Beavers have large skulls and powerful chewing muscles. They have four chisel-shaped incisors that continue to grow throughout their lives. The incisors are covered in a thick enamel that is colored orange or reddish-brown by iron compounds. The lower incisors have roots that are almost as long as the entire lower jaw. Beavers have one premolar and three molars on all four sides of the jaws, adding up to 20 teeth. The molars have meandering ridges for grinding woody material. The eyes, ears and nostrils are arranged so that they can remain above water while the rest of the body is submerged. The nostrils and ears have valves that close underwater, while nictitating membranes cover the eyes. To protect the larynx and trachea from water flow, the epiglottis is contained within the nasal cavity instead of the throat. In addition, the back of the tongue can rise and create a waterproof seal. A beaver's lips can close behind the incisors, preventing water from entering their mouths as they cut and bite onto things while submerged.
Answer: - Large skulls
-Four chisel shaped incisors covered in thick orange or reddish-brown enamel
- One premolar and three molars on all four sides of the jaw
- Nostril valves that close underwater
- Membranes that can cover the eyes underwater
Question: Identify which animal species is alive or extinct: Aurochs, Hawksbill Turtle
Answer: Hawksbill Turtle is alive, Aurochs is extinct.
Question: How many bridges are in the Florida Keys?
Answer: A modern wonder, the 113 miles of roadway from Key Largo to Key West incorporates an astonishing 42 bridges leapfrogging from key to key in a series of giant arches of concrete and steel over the open waters of the Atlantic Ocean, Florida Bay and the Gulf of Mexico.
Question: Extract the names of the founders of Genoa C.F.C from the text?
Evidence: In Italy, Genoa C.F.C. is the oldest active football club: it was founded by Charles De Grave Sells, S. Green, George Blake, W. Rilley, George Dormer Fawcus, H.M. Sandys, E. De Thierry, Johnathan Summerhill Sr., Johnathan Summerhill Jr. and Sir Charles Alfred Payton in Genoa on 7 September 1893. However, Genoa C.F.C. was not the first Italian football club, being Torino Football & Cricket Club (1887) but its history lasted only for 4 years. Founded by Edoardo Bosio (owner of Bosio & Caratsch, the earliest brewery in Italy), the team broke up in 1891. Older than Genoa and Torino is Associazione Sportiva Dilettantistica Fanfulla, a sports club founded in Lodi in 1873, but its football section was established thirty-five years later in 1908.
Answer: The founders of Genoa C.F.C are Charles De Grave Sells, S. Green, George Blake, W. Rilley, George Dormer Fawcus, H.M. Sandys, E. De Thierry, Johnathan Summerhill Sr., Johnathan Summerhill Jr. and Sir Charles Alfred Payton.
Question: What kind of salt should I use while cooking?
Answer: The type of salt used in cooking may vary by recipe as well as intended purpose.  Here are some suggestions for types of salt to use.  For daily use in a typical salt shaker, iodized table salt is the most common as it is processed to be free-flowing and fits through most salt shaker lids with ease.  For brining and during the cooking process most chefs and cooks will choose to only use kosher salt due to it’s flake size and consistency across recipes but they will typically choose one particular brand and stick with it.  For finishing a dish with salt, chefs will also choose a large crystal sea salt usually pyramid shaped as it delivers a satisfying crunch and flavor to the final dish.  Himalayan pink salt has also become popular for use as a finishing salt.
Question: Is the dataset multilingual?
Evidence: We use a new dataset of GD statements from 1970 to 2016, the UN General Debate Corpus (UNGDC), to examine the international development agenda in the UN BIBREF3 . Our application of NLP to these statements focuses in particular on structural topic models (STMs) BIBREF4 . The paper makes two contributions using this approach: (1) It sheds light on the main international development issues that governments prioritise in the UN; and (2) It identifies the key country-specific factors associated with governments discussing development issues in their GD statements.
We use a new dataset of GD statements from 1970 to 2016, the UN General Debate Corpus (UNGDC), to examine the international development agenda in the UN BIBREF3 . 
Answer: No.
Question: What is Star Alliance
Answer: Star Alliance is the world's largest global airline alliance. Founded on 14 May, 1997, its headquarters are located in Frankfurt am Main, Germany, and Jeffrey Goh is its CEO. As of April 2018, Star Alliance is the largest of the three global alliances by passenger count with 762.27 million, ahead of both SkyTeam (630 million) and Oneworld (528 million). Its slogan is "The Way the Earth Connects".

Star Alliance's 26 member airlines operate a fleet of ~5,033 aircraft, serving more than 1,290 airports in 195 countries on more than 19,000 daily departures. The alliance has a two-tier rewards program, Silver and Gold, with incentives including priority boarding and upgrades. Like other airline alliances, Star Alliance airlines share airport terminals (known as co-locations), and many member planes are painted in the alliance's livery.
Question: Given this paragraph about John C. Young, where did he go to college?
Evidence: John Clarke Young (August 12, 1803 – June 23, 1857) was an American educator and pastor who was the fourth president of Centre College in Danville, Kentucky. A graduate of Dickinson College and Princeton Theological Seminary, he entered the ministry in Lexington, Kentucky, in 1828. He accepted the presidency of Centre College in 1830, holding the position until his death in 1857, making him the longest-serving president in the college's history. He is regarded as one of the college's best presidents, as he increased the endowment of the college more than five-fold during his term, and increased the graduating class size from two students in his first year to forty-seven in his final year.
Answer: Dickinson College and Princeton Theological Seminary
Question: What public health inventions did Louis Pasteur contribute to society?
Answer: Louis Pasteur is famous for the discovery of the pasteurization process and vaccination methods
Question: What languages are included in the dataset?
Evidence: For our classification experiments, we use the MH17 Twitter dataset introduced by BIBREF4, a dataset collected in order to study the flow of (dis)information about the MH17 plane crash on Twitter. It contains tweets collected based on keyword search that were posted between July 17, 2014 (the day of the plane crash) and December 9, 2016.
BIBREF4 provide annotations for a subset of the English tweets contained in the dataset. A tweet is annotated with one of three classes that indicate the framing of the tweet with respect to responsibility for the plane crash. A tweet can either be pro-Russian (Ukrainian authorities, NATO or EU countries are explicitly or implicitly held responsible, or the tweet states that Russia is not responsible), pro-Ukrainian (the Russian Federation or Russian separatists in Ukraine are explicitly or implicitly held responsible, or the tweet states that Ukraine is not responsible) or neutral (neither Ukraine nor Russia or any others are blamed). Example tweets for each category can be found in Table TABREF9. These examples illustrate that the framing annotations do not reflect general polarity, but polarity with respect to responsibility to the crash. For example, even though the last example in the table is in general pro-Ukrainian, as it displays the separatists in a bad light, the tweet does not focus on responsibility for the crash. Hence the it is labeled as neutral. Table TABREF8 shows the label distribution of the annotated portion of the data as well as the total amount of original tweets, and original tweets plus their retweets/duplicates in the network. A retweet is a repost of another user's original tweet, indicated by a specific syntax (RT @username: ). We consider as duplicate a tweet with text that is identical to an original tweet after preprocessing (see Section SECREF18). For our classification experiments, we exclusively consider original tweets, but model predictions can then be propagated to retweets and duplicates.
For our classification experiments, we use the MH17 Twitter dataset introduced by BIBREF4, a dataset collected in order to study the flow of (dis)information about the MH17 plane crash on Twitter. It contains tweets collected based on keyword search that were posted between July 17, 2014 (the day of the plane crash) and December 9, 2016.

BIBREF4 provide annotations for a subset of the English tweets contained in the dataset.
Answer: The answers are shown as follows:
* English
Question: How many sexes are there and how many genders are there and what's the difference?
Answer: There are two sexes - male and female, and three genders - male, female, and other. The other gender includes non-binary genders, such as agender, genderqueer, androgynous, and intersex. There are many different gender identities, including male, female, transgender, gender neutral, non-binary, agender, pangender, genderqueer, two-spirit, third gender, and all, none or a combination of these.
Question: How to become a good team player?
Answer: To become a good team player, one needs to be:
Considerate to other team members and
Willing to help and go above and beyond to help teammates
Not only that, they actually should instill a positive attitude towards all team members and be always ready to help and leave things better then it was
There is no "i" in team