DataHammer/scimrc huggingface dataset:
Question: Given this paragraph about Singapore, who was Singapore's first president?
Evidence: After being expelled from Malaysia, Singapore became independent as the Republic of Singapore on 9 August 1965, with Lee Kuan Yew and Yusof bin Ishak as the first prime minister and president respectively. In 1967, the country co-founded the Association of Southeast Asian Nations (ASEAN). Race riots broke out once more in 1969. Lee Kuan Yew's emphasis on rapid economic growth, support for business entrepreneurship, and limitations on internal democracy shaped Singapore's policies for the next half-century. Economic growth continued throughout the 1980s, with the unemployment rate falling to 3% and real GDP growth averaging at about 8% up until 1999. During the 1980s, Singapore began to shift towards high-tech industries, such as the wafer fabrication sector, in order to remain competitive as neighbouring countries began manufacturing with cheaper labour. Singapore Changi Airport was opened in 1981 and Singapore Airlines was formed. The Port of Singapore became one of the world's busiest ports and the service and tourism industries also grew immensely during this period.
Answer: Yusof bin Ishak
Question: Extract all of the names of people mentioned in this paragraph and list them using bullets in the format {Name}
Evidence: Formed in 1888, the program has 856 wins and claims 11 national championships, including 8 from the major wire-service (AP, Coaches'), heading into the 2022 season. USC has had 13 undefeated seasons including 8 perfect seasons, and 39 conference championships. USC has produced eight Heisman Trophy winners, 81 first-team Consensus All-Americans, including 29 Unanimous selections, and 510 NFL draft picks, most all-time by any university, USC has had 35 members inducted into the College Football Hall of Fame, including former players Matt Leinart, O. J. Simpson, and Ronnie Lott and former coaches John McKay and Howard Jones. The Trojans boast 14 inductees in the Pro Football Hall of Fame, the most of any school, including Junior Seau, Bruce Matthews, Marcus Allen, and Ron Yary. Among all colleges and universities, as of 2022, USC holds the all-time record for the most quarterbacks (17) and is tied with the University of Miami for the most wide receivers (40) to go on to play in the NFL.
Answer: • Matt Leinart
• O. J. Simpson
• Ronnie Lott
• John McKay
• Howard Jones
• Junior Seau
• Bruce Matthews
• Marcus Allen
• Ron Yary
Question: What are some different festivities people do on Easter?
Answer: Egg hunt, egg dyeing, Easter baskets, photos with the Easter bunny
Question: Give me a list of Indian dishes that I can make for a house party
Answer: Some popular Indian dishes that you can consider for a house party can be:
- Pav Bhaji 
- Paneer Tikka Masala 
- Butten Chicken 
- Gol Gappe 
- Palak Paneer 
- Vindaloo 
- Chicken Biryani 
- Garlic Naan
- Yellow Daal or Daal Tadka 
- Black Daal 

Be sure to pair it with some popular indian drinks like 
- Mango Lassi 
- Chai 
- Lemon Sherbet 
- Kingfisher Beer
Question: Give me a list of nice board games to play with friends
Answer: 1. Cards Against Humanity
2. Codenames
3. The Game of Things
4. Taboo
5. Balderdash
6. Scattergories
7. Exploding Kittens
Question: What is novel in author's approach?
Evidence: Our novelties include:
Using self-play learning for the neural response ranker (described in detail below).
Optimizing neural models for specific metrics (e.g. diversity, coherence) in our ensemble setup.
Training a separate dialog model for each user, personalizing our socialbot and making it more consistent.
Using a response classification predictor and a response classifier to predict and control aspects of responses such as sentiment, topic, offensiveness, diversity etc.
Using a model predictor to predict the best responding model, before the response candidates are generated, reducing computational expenses.
Using our entropy-based filtering technique to filter all dialog datasets, obtaining higher quality training data BIBREF3.
Building big, pre-trained, hierarchical BERT and GPT dialog models BIBREF6, BIBREF7, BIBREF8.
Constantly monitoring the user input through our automatic metrics, ensuring that the user stays engaged.
Our novelties include:

Using self-play learning for the neural response ranker (described in detail below).

Optimizing neural models for specific metrics (e.g. diversity, coherence) in our ensemble setup.

Training a separate dialog model for each user, personalizing our socialbot and making it more consistent.

Using a response classification predictor and a response classifier to predict and control aspects of responses such as sentiment, topic, offensiveness, diversity etc.

Using a model predictor to predict the best responding model, before the response candidates are generated, reducing computational expenses.

Using our entropy-based filtering technique to filter all dialog datasets, obtaining higher quality training data BIBREF3.

Building big, pre-trained, hierarchical BERT and GPT dialog models BIBREF6, BIBREF7, BIBREF8.

Constantly monitoring the user input through our automatic metrics, ensuring that the user stays engaged.
Answer: They use self-play learning , optimize the model for specific metrics, train separate models per user, use model  and response classification predictors, and filter the dataset to obtain higher quality training data.
Question: what crowdsourcing platform is used?
Evidence: Given the full text of a scientific publication, we want to rank its citations according to the author's judgments. We collected recent publications from the open-access PLoS journals and asked the authors to rank by closeness five citations we selected from their paper. PLoS articles were selected because its journals cover a wide array of topics and the full text articles are available in XML format. We selected the most recent publications as previous work in crowd-sourcing annotation shows that authors' willingness to participate in an unpaid annotation task declines with the age of publication ( BIBREF23 ). We then extracted the abstract, citations, full text, authors, and corresponding author email address from each document. The titles and abstracts of the citations were retrieved from PubMed, and the cosine similarity between the PLoS abstract and the citation's abstract was calculated. We selected the top five most similar abstracts using TF*IDF weighted cosine similarity, shuffled their order, and emailed them to the corresponding author for annotation. We believe that ranking five articles (rather than the entire collection of the references) is a more manageable task for an author compared to asking them to rank all references. Because the documents to be annotated were selected based on text similarity, they also represent a challenging baseline for models based on text-similarity features. In total 416 authors were contacted, and 92 responded (22% response rate). Two responses were removed from the dataset for incomplete annotation.
Given the full text of a scientific publication, we want to rank its citations according to the author's judgments. We collected recent publications from the open-access PLoS journals and asked the authors to rank by closeness five citations we selected from their paper.
Answer: The answers are shown as follows:
* asked the authors to rank by closeness five citations we selected from their paper
Question: What are puns?
Evidence: Puns are a form of wordplay jokes in which one sign (e.g. a word or a phrase) suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another sign, for an intended humorous or rhetorical effect BIBREF3 . Puns where the two meanings share the same pronunciation are known as homophonic or perfect puns, while those relying on similar but non-identical sounding words are known as heterophonic BIBREF4 or imperfect puns BIBREF5 . In this paper, we study automatic target recoverability of English-Hindi code mixed puns - which are more commonly imperfect puns, but may also be perfect puns in some cases.
Puns are a form of wordplay jokes in which one sign (e.g. a word or a phrase) suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another sign, for an intended humorous or rhetorical effect BIBREF3 .
Answer: The answers are shown as follows:
* a form of wordplay jokes in which one sign (e.g. a word or a phrase) suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another sign, for an intended humorous or rhetorical effect
Question: Out of the following, which one is not a movie: The God Father, Fight Club, Gladiator,  One Hundred Years of Solitude, and Big Fish.
Answer: The correct answer is Hundred Years of Solitude. It is a popular book written by Gabriel Garcia Marquez.
Question: Is the mascot for the University of Colorado a real buffalo?
Answer: Indeed, Ralphie is a real buffalo. She is the fifth live Buffalo mascot for the University of Colorado in Boulder, CO. She lives in an undisclosed location and makes an appearance at every home football game, running a horseshoe shape from one side of the endzone around the perimeter of the field into a trailer on the other side of the same endzone. She is managed by a team of student handlers who go through a rigorous tryout program to join her team.
Question: What are some Asian fusion lunches that are a one-bowl style meal? Please list the ingredients for each idea and include at least one vegetarian option.
Answer: Some ideas for Asian fusion bowl lunches are as follows:
- Tokyo bowl - Chicken, rice, scallions, furikake, mushrooms, radishes, cucumber salad and smoked teriyaki sauce 
- California bowl - Crispy tofu, rice, avocado, bean sprouts, mushrooms, pickled red onions, furikake, kale, Japanese mayo
- Penang bowl - Chicken, rice, cilantro, sambal, scallions, cucumber salad and peanut curry sauce
- Seoul bowl - Beef, rice, kimchi, scallions, bonito flakes, sesame seeds, bean sprouts, cucumber salad and gochujang
- Shanghai bowl - Shrimp, rice, scallions, sesame seeds, Chinese broccoli with mushrooms and five spice sauce
- Bangkok bowl - Shrimp, rice, mangoes, shallots, garlic, peanuts, scallions, cilantro, shrimp sambal, lime fish sauce, Thai chilies
Question: Which of the following are types of real estate assets: single family homes, multi-family homes, apartments, condos, townhomes, rocks, dirt, cars, diamonds, gold, land, water, doors.
Answer: Real estate assets are typically land or improvements made on top of land. From the list, this includes single family homes, multi-family homes, apartments, condos, townhomes, and land.
Question: Tell me about the Film carreer in points of actress Richa Soni
Evidence: Richa Soni is an Indian television actress. She made her debut in Shararat. She is known for her role of Bindiya in the ColorTV's daily soap Bhagyavidhaata . She has also appeared in shows like, Nachle Ve With Saroj Khan - Season 2, Badalte Rishton Ki Dastaan, Jaat Ki Jugni and Siya Ke Ram. She has also done short films like The Silent Statue (showcased in Cannes Film Festival and she also won the Award for "Best Actress in the Short Films Category" in the 2nd Jharkhand International Film Festival 2019. The web series Seasoned with Love premiered on Hungama Play on 16 April 2019.
Answer: 1. Richa Soni is an Indian actress who works in television.
2. In Shararat, she made her acting debut.
3. She is well-known for playing Bindiya in the daily soap opera Bhagyavidhaata on ColorTV.
4. She has also made appearances in episodes like Siya Ke Ram, Badalte Rishton Ki Dastaan, Jaat Ki Jugni, and Nachle Ve With Saroj Khan - Season 2.
5. She has also produced short films, including The Silent Statue, which premiered at the Cannes Film Festival and received the 2019 2nd Jharkhand International Film Festival's award for "Best Actress in the Short Films Category."
6. On April 16, 2019, Hungama Play hosted the world premiere of the online series Seasoned with Love.
Question: Summarize the three laws of thermodynamics in one or two sentences each. They should be understandable by a layman.
Evidence: The laws of thermodynamics are a set of scientific laws which define a group of physical quantities, such as temperature, energy, and entropy, that characterize thermodynamic systems in thermodynamic equilibrium. The laws also use various parameters for thermodynamic processes, such as thermodynamic work and heat, and establish relationships between them. They state empirical facts that form a basis of precluding the possibility of certain phenomena, such as perpetual motion. In addition to their use in thermodynamics, they are important fundamental laws of physics in general, and are applicable in other natural sciences.

Traditionally, thermodynamics has recognized three fundamental laws, simply named by an ordinal identification, the first law, the second law, and the third law. A more fundamental statement was later labelled as the zeroth law, after the first three laws had been established.

The zeroth law of thermodynamics defines thermal equilibrium and forms a basis for the definition of temperature: If two systems are each in thermal equilibrium with a third system, then they are in thermal equilibrium with each other.

The first law of thermodynamics states that, when energy passes into or out of a system (as work, heat, or matter), the system's internal energy changes in accordance with the law of conservation of energy.

The second law of thermodynamics states that in a natural thermodynamic process, the sum of the entropies of the interacting thermodynamic systems never decreases. A common corollary of the statement is that heat does not spontaneously pass from a colder body to a warmer body.

The third law of thermodynamics states that a system's entropy approaches a constant value as the temperature approaches absolute zero. With the exception of non-crystalline solids (glasses), the entropy of a system at absolute zero is typically close to zero.

The first and second laws prohibit two kinds of perpetual motion machines, respectively: the perpetual motion machine of the first kind which produces work with no energy input, and the perpetual motion machine of the second kind which spontaneously converts thermal energy into mechanical work.
Answer: The first law states that energy in a closed system is conserved. More energy than that which was present cannot be created, nor can some energy be destroyed.

The second law says heat moves from a warm to a cold body. 

The third law says the entropy of a system is related to it's temperature, and decreases as temperature decreases.
Question: What is the lowest point on Earth?
Answer: The Challenger Deep, located in the western Pacific Ocean is the deepest known point of the seabed of Earth, with a depth of 10,902 -10,929 m or 35,768 - 35,856 ft.
Question: What are results of public code repository study?
Evidence: How do non-English speakers program in a language like Java, where the keywords and core libraries are written in English? We employ a data driven approach to tell the story of non-English code and inform the decisions we made in our auto-translator. We analyzed Java repositories on GitHub, the largest host of source code in the world, where 1.1 million unique users host 2.9 million public Java projects. We downloaded and analyzed the human language used for writing comments (in Java code), naming identifiers (method and variable names), and writing git commit messages. We focused on Java code as it is both one of the most popular source-code languages on GitHub and in the classroom. A selection of results from this study are that:
Non-English code is a large-scale phenomena.
Transliteration is common in identifiers for all languages.
Languages clusters into three distinct groups based on how speakers use identifiers/comments/transliteration.
Non-latin script users write comments in their L1 script but write identifiers in English.
Right-to-left (RTL) language scripts, such as Arabic, have no observed prevalence on GitHub identifiers, implying that existing coders who speak RTL languages have substantial barriers in using their native script in code.
A selection of results from this study are that:

Non-English code is a large-scale phenomena.

Transliteration is common in identifiers for all languages.

Languages clusters into three distinct groups based on how speakers use identifiers/comments/transliteration.

Non-latin script users write comments in their L1 script but write identifiers in English.

Right-to-left (RTL) language scripts, such as Arabic, have no observed prevalence on GitHub identifiers, implying that existing coders who speak RTL languages have substantial barriers in using their native script in code.
Answer: The answers are shown as follows:
* Non-English code is a large-scale phenomena.
* Transliteration is common in identifiers for all languages.
* Languages clusters into three distinct groups based on how speakers use identifiers/comments/transliteration.
* Non-latin script users write comments in their L1 script but write identifiers in English.
* Right-to-left (RTL) language scripts, such as Arabic, have no observed prevalence on GitHub identifiers
Question: Please list the harm that air pollution caused based on the given passage.
Evidence: Air pollution is the contamination of air due to the presence of substances in the atmosphere that are harmful to the health of humans and other living beings, or cause damage to the climate or to materials. It is also the contamination of indoor or outdoor surrounding either by chemical activities, physical or biological agents that alters the natural features of the atmosphere. There are many different types of air pollutants, such as gases (including ammonia, carbon monoxide, sulphur dioxide, nitrous oxides, methane, carbon dioxide and chlorofluorocarbons), particulates (both organic and inorganic), and biological molecules. Air pollution can cause diseases, allergies, and even death to humans; it can also cause harm to other living organisms such as animals and food crops, and may damage the natural environment (for example, climate change, ozone depletion or habitat degradation) or built environment (for example, acid rain).  Air pollution can be caused by both human activities and natural phenomena.
Answer: 1.	Air pollution is caused by the presence of harmful substances in the air, it can cause damage to human health, living beings and climate.
2.	Air pollution can cause diseases, allergies and even death to human, it can also harm animals, food corp and the nature.
3.	Air pollution can harm the natural environment by climate change, ozone depletion, habitat degradation ,acid rain.
Question: How tall is 970 Park Ave?
Evidence: 970 Park Avenue is a luxury residential housing cooperative in Manhattan, New York City.

970 was designed by the New York architectural firm of Schwartz & Gross and built by the developers Bing & Bing. It is located on Park Avenue and East 83rd Street.

The 12-story building was erected in 1912. In 1940, the bank that owned the building reconfigured the building, altering the original spacious apartments into smaller units. In 1987, it was converted to a cooperative by Martin J. Raynes; Raynes added two triplex penthouses with "greenhouse" studies, circular staircases and large terraces. The building stands at 132 feet (40 m) tall.
Answer: 970 Park Avenue is a 12-story building that stands 132 feet (40m) tall.
Question: Which of the following are actual titles for albums by Led Zeppelin?

Houses of the Holy, Stairway to Heaven, Zoso, Led Zeppelin III, In Through the Out Door, Presents
Answer: The correct answer is Houses of the Holy, Led Zeppelin III and In Through the Out Door. Stairway to Heaven is a song title but not an album title. Zoso is commonly incorrectly used as the album title of Led Zeppelin IV. And while Presents is incorrect, there is a Led Zeppelin album entitled Presence.
Question: Which translation system do they use to translate to English?
Evidence: Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model. It divides translation process into two steps. First, in the encoder step, given an input sentence INLINEFORM0 of length INLINEFORM1 , INLINEFORM2 represents each word as word embedding INLINEFORM3 . After that, we obtain the absolute position of input elements INLINEFORM4 . Both vectors are concatenated to get input sentence representations INLINEFORM5 . Similarly, output elements INLINEFORM6 generated from decoder network have the same structure. A convolutional neural network (CNN) is used to get the hidden state of the sentence representation from left to right. Second, in the decoder step, attention mechanism is used in each CNN layer. In order to acquire the attention value, we combine the current decoder state INLINEFORM7 with the embedding of previous decoder output value INLINEFORM8 : DISPLAYFORM0
Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model.
Answer: Attention-based translation model with convolution sequence to sequence model
Question: In addition to the tweet data provided by the task organizers, do they use any other datasets?
Evidence: The tweet data was provided by the task organizers. It consists of 106 hashtag files made up of about 21,000 tokens. The hashtag files were further divided into a development set trial_dir of 6 hashtags and a training set of 100 hashtags train_dir. We also obtained 6.2 GB of English news data with about two million tokens from the News Commentary Corpus and the News Crawl Corpus from 2008, 2010 and 2011. Each tweet and each sentence from the news data is found on a single line in their respective files.
During the development of our system we trained our language models solely on the 100 hashtag files from train_dir and then evaluated our performance on the 6 hashtag files found in trial_dir. That data was formatted such that each tweet was found on a single line.
Pre-processing consists of two steps: filtering and tokenization. The filtering step was only for the tweet training corpus. We experimented with various filtering and tokenziation combinations during the development stage to determine the best setting.
Filtering removes the following elements from the tweets: URLs, tokens starting with the “@” symbol (Twitter user names), and tokens starting with the “#” symbol (Hashtags).
Tokenization: Text in all training data was split on white space and punctuation
The tweet data was provided by the task organizers. It consists of 106 hashtag files made up of about 21,000 tokens. The hashtag files were further divided into a development set trial dir of 6 hashtags and a training set of 100 hashtags train dir. We also obtained 6.2 GB of English news data with about two million tokens from the News Commentary Corpus and the News Crawl Corpus from 2008, 2010 and 20112 . Each tweet and each sentence from the news data is found on a single line in their respective files.
Answer: Yes, the News Commentary Corpus and the News Crawl Corpus.
Question: What are the top 10 songs on the Billboard Year End list from 1987?
Answer: The top 10 songs from the Billboard Year-End Hot 100 singles of 1987 are as follows:

1.	"Walk Like An Egyptian", The Bangles
2.	"Alone", Heart
3.	"Shake You Down", Gregory Abbott
4.	"I Wanna Dance with Somebody (Who Loves Me)", Whitney Houston
5.	"Nothing's Gonna Stop Us Now", Starship
6.	"C'est La Vie", Robbie Nevil
7.	"Here I Go Again", Whitesnake
8.	"The Way It Is", Bruce Hornsby and the Range
9.	"Shakedown", Bob Seger
10.	"Livin' on a Prayer", Bon Jovi