DataHammer/scimrc huggingface dataset:
Question: What datasets do they use?
Evidence: We work with four individual datasets. The datasets contain addition, subtraction, multiplication, and division word problems.
AI2 BIBREF2. AI2 is a collection of 395 addition and subtraction problems, containing numeric values, where some may not be relevant to the question.
CC BIBREF19. The Common Core dataset contains 600 2-step questions. The Cognitive Computation Group at the University of Pennsylvania gathered these questions.
IL BIBREF4. The Illinois dataset contains 562 1-step algebra word questions. The Cognitive Computation Group compiled these questions also.
MAWPS BIBREF20. MAWPS is a relatively large collection, primarily from other MWP datasets. We use 2,373 of 3,915 MWPs from this set. The problems not used were more complex problems that generate systems of equations. We exclude such problems because generating systems of equations is not our focus.
We work with four individual datasets. The datasets contain addition, subtraction, multiplication, and division word problems.

AI2 BIBREF2. AI2 is a collection of 395 addition and subtraction problems, containing numeric values, where some may not be relevant to the question.

CC BIBREF19. The Common Core dataset contains 600 2-step questions. The Cognitive Computation Group at the University of Pennsylvania gathered these questions.

IL BIBREF4. The Illinois dataset contains 562 1-step algebra word questions. The Cognitive Computation Group compiled these questions also.

MAWPS BIBREF20. MAWPS is a relatively large collection, primarily from other MWP datasets. We use 2,373 of 3,915 MWPs from this set.
Answer: The answers are shown as follows:
* AI2 BIBREF2
* CC BIBREF19
* IL BIBREF4
* MAWPS BIBREF20
Question: What are some interactive toys for toddlers?
Answer: Toddlers love to play with all varieties of toys - sensory, building, imaginative, and more. For an interactive and engaging experience, some of the greatest toys for toddlers are legos, magna tiles, playdoh, and kinetic sand. These activities and toys give them the creative freedom to use their imagination and fine motor skills.
Question: Which parks are popular in London?
Evidence: A 2013 report by the City of London Corporation said that London is the "greenest city" in Europe with 14,164 hectares (35,000 acres) of public parks, woodlands and gardens. The largest parks in the central area of London are three of the eight Royal Parks, namely Hyde Park and its neighbour Kensington Gardens in the west, and Regent's Park to the north. Hyde Park in particular is popular for sports and sometimes hosts open-air concerts. Regent's Park contains London Zoo, the world's oldest scientific zoo, and is near Madame Tussauds Wax Museum. Primrose Hill, immediately to the north of Regent's Park, at 256 feet (78 m) is a popular spot from which to view the city skyline.
Answer: Popular parks in London includes Hyde Park, Regent's Park and Kensington Gardens.
Question: What watch should I buy?
Answer: Purchasing a wristwatch is based on your individual desires, preferences and budget. You can purchase ultra high end watches like Patek Phillipe, Rolex and Richard Mille. There are popular tool watches such as Omega Seamaster and the Rolex Submariner which are both great starter watches for collectors. Watch prices vary based on price, materials and the movement. Quartz movement has become a popular alternative to Automatic or Manual watches however watch enthusiasts prefer to have a self-winding watch.
Question: Name a song written by Hank Williams?
Answer: "I'm a Long Gone Daddy" is a country song written and recorded by Hank Williams. It was released in 1948 on MGM Records and became his second top ten hit.
Question: What is a 4x4?
Answer: A 4x4 is a type of vehicle with four wheel drive. It is also know as a SUV, a sports utility vehicle. They are typically higher off the ground than standard cars, with more room inside the cabin. 4x4s typically are heavier with poorer handling, but have the capacity to drive off-road and cope with poor weather conditions much better.
Question: A triangle has angles of 25 degrees and 45 degrees. What is the last angle in the triangle?
Answer: The angles in a triangle sum up to 180 degrees. The last angle is thus 180 - 45 - 25 = 110 degrees
Question: What do I use a pressure washer for?
Answer: A pressure washer forces water out at high speeds which allows you to remove grime or dirt from large surfaces, often of a home or building.
Question: How do they clean their text data in the language model?
Evidence: Our language model training pipeline is described in Figure FIGREF6. First, we collect and clean large amount of text data from various sources including news, manual labeled conversation video. Then, the collected data is categorized into domains. This is an important step as the ASR performance is highly depends on the speech domain. After that, the text is fed into a data cleaning pipeline to clean bad tone marks, normalizing numbers and dates.
For each domain text data, we train an n-gram language modelBIBREF1 that is optimized for that domain. As the results, we have more than 10 language models. These language models are combined based on perplexity calculated on a small text of a domain that we want to optimize for.
In our system, the language model is used in 2 pass-decoding. In the first pass, the language model is combined with acoustic and lexicon model to form a full decoding graph. In this stage, the language model is typically small in size by utilizing pruning method. In the second stage, we use a un-pruned language model to rescore decoded lattices.
Our language model training pipeline is described in Figure 1. First, we collect and clean large amount of text data from various sources including news, manual labeled conversation video. Then, the collected data is categorized into domains. This is an important step as the ASR performance is highly depends on the speech domain. After that, the text is fed into a data cleaning pipeline to clean bad tone marks, normalizing numbers and dates.
Answer: Categorize the text data from various sources that have been cleaned into domains and then clean bad tone marks, normalizing numbers, and dates.
Question: What is the difference between the words ‘this’ and ‘that’?
Answer: The difference between ‘this’ and ‘that’ has to do with proximity.  When referring to something that is in close proximity you would use the word ‘this’: “This finger hurts me the most.”  Conversely, if something far away you would use the word that: “That hill off in the distance is called the Blue Hills.”
Question: Based on this paragraph about the Final Fantasy series, who created it?
Evidence: Final Fantasy is a Japanese science fantasy anthology media franchise created by Hironobu Sakaguchi and developed and owned by Square Enix (formerly Square). The franchise centers on a series of fantasy and science fantasy role-playing video games. The first game in the series was released in 1987, with 15 numbered main entries having been released to date.
Answer: Hironobu Sakaguchi
Question: Given this paragraph about Eric Clapton, what solo accomplishments help rank him as one of the most influential guitarists of all time?
Evidence: Clapton has been referred to as one of the most important and influential guitarists of all time. Clapton is the only three-time inductee to the Rock and Roll Hall of Fame: once as a solo artist, and separately as a member of the Yardbirds and Cream. He ranked second in Rolling Stone magazine's list of the "100 Greatest Guitarists of All Time" and fourth in Gibson's Top 50 Guitarists of All Time.
Answer: Inductee as a solo artist into the Rock and Roll Hall of Fame; 
Ranking 2nd in Rolling Stone Magazine's  list of the "100 Greatest Guitarists of All Time;" Ranking 4th in Gibson's Top 50 Guitarists of All Time
Question: What are some must-see places in Romania?
Answer: There are a lot of beautiful places to see in Romania, so it is really hard to gather them all. On a must-see list you should include cities like Brasov, Sibiu, Sighisoara. If you like driving, you should check some beautiful roads like Transfagarasan or Transalpina. If you like hiking, you must consider Fagaras mountains.
Question: How do solar panels work?
Answer: Sunlight contains photon particles which hit the solar panels and cause electrons off silicon chips to get directed to the wiring to batteries or appliances, providing electricity
Question: Given a reference text about the Falcons, how many Super Bowls have they won in their history?
Evidence: The Atlanta Falcons are a professional American football team based in Atlanta. The Falcons compete in the National Football League (NFL) as a member club of the league's National Football Conference (NFC) South division. The Falcons were founded on June 30, 1965, and joined the NFL in 1966 as an expansion team, after the NFL offered then-owner Rankin Smith a franchise to keep him from joining the rival American Football League (AFL).

In their 55 years of existence, the Falcons have compiled a record of 379–487–6 (369–473–6 in the regular season and 10–14 in the playoffs), winning division championships in 1980, 1998, 2004, 2010, 2012, and 2016. The Falcons have appeared in two Super Bowls, the first during the 1998 season in Super Bowl XXXIII, where they lost to the Denver Broncos 34–19, and the second 18 years later, a 34–28 overtime loss to the New England Patriots in Super Bowl LI.

The Falcons' current home field is Mercedes-Benz Stadium, which opened for the 2017 season; the team's headquarters and practice facilities are located at a 50-acre (20 ha) site in Flowery Branch, northeast of Atlanta in Hall County.
Answer: Although the falcons have been to two Super Bowl games in their history, they have not won a Super Bowl yet.
Question: If my car's fuel tank fits 18 gallon, how many times do I need to refuel on a 10-hour trip if the average speed is 60mph and the car's fuel efficiency is 30mpg?
Answer: Assuming the tank is full when you start, you would have to refuel once. 10 hours at 60mph means the total distance is 600 miles. To drive 600 miles at a fuel efficiency of 30 mpg you would need 20 gallons of fuel. That's more than the 18 gallon capacity of the tank, but less than twice the capacity, so you would need to refuel once.
Question: Based on this paragraph about the Ming treasure voyages, who commanded the fleet?
Evidence: The Ming treasure voyages were the seven maritime expeditions undertaken by Ming China's treasure fleet between 1405 and 1433. The Yongle Emperor ordered the construction of the treasure fleet in 1403. The grand project resulted in far-reaching ocean voyages to the coastal territories and islands in and around the South China Sea, the Indian Ocean, and beyond. Admiral Zheng He was commissioned to command the treasure fleet for the expeditions. Six of the voyages occurred during the Yongle reign (r. 1402–24), while the seventh voyage occurred during the Xuande reign (r. 1425–1435). The first three voyages reached up to Calicut on India's Malabar Coast, while the fourth voyage went as far as Hormuz in the Persian Gulf. In the last three voyages, the fleet traveled up to the Arabian Peninsula and East Africa.
Answer: Based on this text, Admiral Zheng He commanded the Ming treasure voyages.
Question: How many sentences does each dataset consist of?
Evidence: It is well-established that gender bias exists in language – for example, we see evidence of this given the prevalence of sexism in abusive language datasets BIBREF0, BIBREF1. However, these are extreme cases of gender norms in language, and only encompass a small proportion of speakers or texts.
Less studied in NLP is how gender norms manifest in everyday language – do people talk about women and men in different ways? These types of differences are far subtler than abusive language, but they can provide valuable insight into the roots of more extreme acts of discrimination. Subtle differences are difficult to observe because each case on its own could be attributed to circumstance, a passing comment or an accidental word. However, at the level of hundreds of thousands of data points, these patterns, if they do exist, become undeniable. Thus, in this work, we introduce new datasets and methods so that we can study subtle gender associations in language at the large-scale.
Our contributions include:
Two datasets for studying language and gender, each consisting of over 300K sentences.
Methods to infer gender-associated words and labeled clusters in any domain.
Novel findings that demonstrate in both domains that people do talk about women and men in different ways.
Each contribution brings us closer to modeling how gender associations appear in everyday language. In the remainder of the paper, we present related work, our data collection, methods and findings, and human evaluations of our system.
Our contributions include: Two datasets for studying language and gender, each consisting of over 300K sentences.
Answer: 300K.
Question: What metric do they use to justify the effectiveness of their method?
Evidence: Both neural and statistical machine translation approaches are highly reliant on the availability of large amounts of data and are known to perform poorly in low resource settings. Recent crowd-sourcing efforts and workshops on machine translation have resulted in small amounts of parallel texts for building viable machine translation systems for low-resource pairs BIBREF0 . But, they have been shown to suffer from low accuracy (incorrect translation) and low coverage (high out-of-vocabulary rates), due to insufficient training data. In this project, we try to address the high OOV rates in low-resource machine translation systems by leveraging the increasing amount of multilingual content available on the Internet for enriching the bilingual lexicon.
Comparable corpora such as Wikipedia, are collections of topic-aligned but non-sentence-aligned multilingual documents which are rich resources for extracting parallel sentences from. For example, Figure FIGREF1 shows that there are equivalent sentences on the page about Donald Trump in Tamil and English, and the phrase alignment for an example sentence is shown in Table TABREF4 .
Table TABREF2 shows that there are at least tens of thousands of bilingual articles on Wikipedia which could potentially have at least as many parallel sentences that could be mined to address the scarcity of parallel sentences as indicated in column 2 which shows the number of sentence-pairs in the largest available bilingual corpora for xx-en. As shown by BIBREF1 ( BIBREF1 ), the illustrated data sparsity can be addressed by extending the scarce parallel sentence-pairs with those automatically extracted from Wikipedia and thereby improving the performance of statistical machine translation systems.
In this paper, we will propose a neural approach to parallel sentence extraction and compare the BLEU scores of machine translation systems with and without the use of the extracted sentence pairs to justify the effectiveness of this method. Compared to previous approaches which require specialized meta-data from document structure or significant amount of hand-engineered features, the neural model for extracting parallel sentences is learned end-to-end using only a small bootstrap set of parallel sentence pairs.
In this paper, we will propose a neural approach to parallel sentence extraction and compare the BLEU scores of machine translation systems with and without the use of the extracted sentence pairs to justify the effectiveness of this method.
Answer: BLEU.
Question: What are the 5 most effective ways to convert a prospect to a customer?
Answer: The journey from cold prospect to loyal customer is as tricky as the alchemy that transforms a stranger into a close personal friend. While there are a thousand possible paths, a handful of methods have proven consistently effective as triggers for moving prospects down the funnel toward purchase.

The first is personal referral. A personal referral or endorsement is worth more than 10,000 words of marketing material. Knowing that someone we know and trust can vouch for a product or service counts for so much that we will instinctually lower our guard and open our ears to a sales pitch.

Second is the testimonial. Like a referral, knowing that someone else -- generally a brand we know or at least can recognize -- uses a product or service predisposes us to try it ourselves. This is especially true of unknown brands or products. Think of when you pass a new restaurant. You may not know the name, the menu or the quality but if there's a crowd inside we naturally assume it must be good. The same goes for a new brand -- when you see others are endorsing it, we relax our natural suspicion and are more willing to give it a try.

Third is the offer. It's not enough to build a great product. You have to overcome people's natural reluctance to open their wallets when you're asking them to pay full price. The offer can take many forms -- from a discount to a free trial to a bonus offer. Adding urgency -- such as a limited quantity or expiration on the offer can also help.

Fourth is the three-step. This works especially well for big-ticket items or purchases that involve a large number of people or disruption to an organization. The 3-step acknowledges that nobody buys a $2,000,000 solution without giving it a lot of thought. So first we simply get them to raise their hand and express interest. This can be done through a top-of-funnel asset like an eBook or webinar. The second step is an offer that gets them more involved with the product, such as a demo. And the third step is a face-to-face meeting with the sales team.

Fifth is third-party validation. Many prospects have an allergic reaction to anything that smells like marketing. But what if they are reading a glowing piece about your. in the Wall Street Journal? Or Gartner places you at the top of one of its magic quadrants? This kind of validation from what is perceived as an objective source carries a lot more weight than marketing content. 

In practice, most businesses use a combination of the five techniques described above. Each will resonate in different ways with prospects; and in combination they can be extremely effective at creating that aura around your company and products that cause the prospect to push the "Buy now" button.
Question: Which three players have the most Masters Victories?
Answer: Jack Nicklaus with 6 victories in 1963, 1965, 1966, 1972, 1975, 1986
Tiger Woods with 5 victories in 1997, 2001, 2002, 2005, 2019
Arnold Palmer with 4 victories in 1958, 1960, 1962, 1964
Question: Given this paragraph about the Mercury Seven. Who did not survive to reach retirement and what was the cause of their death?
Evidence: The Mercury Seven were the group of seven astronauts selected to fly spacecraft for Project Mercury. They are also referred to as the Original Seven and Astronaut Group 1. Their names were publicly announced by NASA on April 9, 1959; these seven original American astronauts were Scott Carpenter, Gordon Cooper, John Glenn, Gus Grissom, Wally Schirra, Alan Shepard, and Deke Slayton. The Mercury Seven created a new profession in the United States, and established the image of the American astronaut for decades to come.

All of the Mercury Seven eventually flew in space. They piloted the six spaceflights of the Mercury program that had an astronaut on board from May 1961 to May 1963, and members of the group flew on all of the NASA human spaceflight programs of the 20th century – Mercury, Gemini, Apollo, and the Space Shuttle.

Shepard became the first American to enter space in 1961, and later walked on the Moon on Apollo 14 in 1971. Grissom flew the first crewed Gemini mission in 1965, but died in 1967 in the Apollo 1 fire; the others all survived past retirement from service. Schirra flew Apollo 7 in 1968, the first crewed Apollo mission, in Grissom's place. Slayton, grounded with an atrial fibrillation, ultimately flew on the Apollo–Soyuz Test Project in 1975. The first American in orbit in 1962, Glenn flew on the Space Shuttle Discovery in 1998 to become, at age 77, the oldest person to fly in space at the time. He was the last living member of the Mercury Seven when he died in 2016 at age 95.
Answer: Only Gus Grissom did not survive to reach retirement. All others survived past retirement from service. The cause of his death is the Apollo 1 fire.
Question: Classify each Taylor Swift album into the respective music genre: Debut, Fearless, Speak Now, Red, 1989, Reputation, Lover, Folklore, Evermore, Midnights
Answer: Debut is country-pop. Fearless is country-pop. Speak Now is Country-pop and Pop-Rock. Red is Country-Pop and Pop-Rock. 1989 is pop. Reputation is electro-pop. Lover is pop. Folklore is Indie folk. Evermore is indie folk. Midnights is electro-pop.
Question: Given this paragraph about a Tesla Model 3, tell me what the EPA-rated ranges are for the various models.
Evidence: The Tesla Model 3 is an electric car produced by American marque Tesla. It is a battery-powered four-door sedan that is considered a mid-size car in the US and a large family car in Europe, and is marketed in the compact-executive segment. Limited production of the Model 3 began in mid-2017, with the first production vehicle rolling off the assembly line on July 7, 2017. The official launch and delivery of the first 30 cars took place on July 28.

The base Model 3 delivers an EPA-rated all-electric range of 272 miles (438 km) and the Long Range version delivers 358 miles (576 km). According to Tesla, the Model 3 carries full self-driving hardware, with periodic software updates adding functionality.

The Model 3 was marketed as being more affordable to more people than previous models by Tesla. Since early 2020, the Model 3 is the bestselling electric car in world history, and, in June 2021, became the first electric car to pass the 1 million global sales milestone. The Model 3 has been the world's top selling plug-in electric car (PEV) for three years running, from 2018 to 2020. It has also been the bestselling PEV in the United States for three consecutive years, 2018 to 2020, the top selling PEV in Europe in 2019, and the bestselling PEV in China in 2020.
Answer: The Tesla Model 3 comes in a base model with a range of 272 miles (438 km) and also comes in a Long Range version that delivers 358 miles (576 km).
Question: Does the proposed low dimensionality representation improve more than 35% of the results obtained with the state-of-the-art representations?
Evidence: In Table 6 we show the results obtained by the described representations employing the Multiclass Classifier. As can be appreciated, the proposed low dimensionality representation improves more than 35% the results obtained with the state-of-the-art representations. BOW obtains slightly better results than character 4-grams, and both of them improve significantly the ones obtained with tf-idf 2-grams. Instead of selecting the most frequent $n$ -grams, our approach takes advantage from the whole vocabulary and assigns higher weights to the most discriminative words for the different language varieties as shown in Equation 10 .
 We highlight that our LDR obtains competitive results compared with the use of distributed representations. Concretely, there is no significant difference among them (Skip-gram $z_{0.05} = 0,5457 < 1,960$ and SenVec $z_{0.05} = 0,7095 < 1,960$ ). In addition, our proposal reduces considerably the dimensionality of one order of magnitude as shown in Table 6 .
As can be appreciated, the proposed low dimensionality representation improves more than 35% the results obtained with the state-of-the-art representations.
Answer: Yes, it does.