DataHammer/scimrc huggingface dataset:
Question: How are racial categories used historically?
Evidence: Racial categories have historically been used as a way to enable an oppressive figure or group to discriminate against other groups or individuals which were seen as different from that of the oppressor. In nineteenth and early twentieth century Europe, artwork was a common form of racialization which targeted countries in the Middle East and Asia. The artwork, predominantly paintings, were portrayed in order to instill prejudice in the Western populations through sexualizing and manipulating images. One of the most prominent examples of Orientalist work in art is a piece by Eugène Delacroix titled Women of Algiers in their Apartment. Dating back to 1834, it portrays three women resting in a harem in exotic clothing while an African woman is dressed in plain clothing, depicting her role as a servant. Fine textiles, hookahs, and other paraphernalia adorn the room, which represents a European fantasy of an exotic scene. Attempts to portray these cultures as strange, foreign and exotic through Orientalism led to intolerance towards the Arab and Asian communities in Europe and the United States. Others argue that Delacroix, who travelled in North Africa sketching extensively, was depicting a realistic scene of the era based on his first-hand knowledge and experience. In such an interpretation the clothing, for example, is consistent with the times, as Arab North Africans dressed differently from Europeans, and kept black slaves who would not have been treated as equals.
Answer: Historically, oppressive groups use racial categories to discriminate against other groups that are different from them.
Question: Do humans have stripes?
Answer: Humans have "stripes" called Blaschko's lines. They are generally invisible to the human eye but some people's lines may be visible due to skin conditions or if they are a chimera, which will cause the lines to express different levels of melanin and make them more readily visible.
Question: Why is UBS and Credit Suisse merging
Evidence: On 19 March 2023, Swiss investment bank UBS Group AG agreed to buy Credit Suisse for CHF 3 billion (US$3.2 billion) in an all-stock deal brokered by the government of Switzerland and the Swiss Financial Market Supervisory Authority. The Swiss National Bank supported the deal by providing more than CHF 100 billion (US$104 billion) in liquidity to UBS following its takeover of Credit Suisse's operations, while the Swiss government provided a guarantee to UBS to cover losses of up to CHF 9 billion (US$9.6 billion) over the short term. Additionally, CHF 16 billion (US$17.2 billion) of Additional Tier 1 bonds were written down to zero.

Credit Suisse is a globally systemically important bank whose investment banking unit, First Boston, had been recently tarnished by a series of high-profile scandals. The banking crisis in the United States had caused fear among global investors and led to panic over other possibly troubled banks. Credit Suisse's share price plunged after the leading shareholder ruled out further investment into the bank due to regulatory issues. The deal was rapidly agreed upon and announced just before the Asian financial markets opened on Monday morning in order to prevent "market shaking" turmoil in the global financial markets. Soon afterward, central banks across the world announced USD liquidity measures to try and ease wider market panic and avoid a wider banking crisis.
Answer: On 19 March 2023, the Swiss wealth management and investment bank UBS Group AG agreed to buy Credit Suisse for CHF 3 billion (US$3.2 billion) in an all-stock deal brokered by the government of Switzerland and the Swiss Financial Market Supervisory Authority. The Swiss National Bank supported the deal by providing more than CHF 100 billion (US$104 billion) in liquidity to UBS following its takeover of Credit Suisse's operations, while the Swiss government provided a guarantee to UBS to cover losses of up to CHF 9 billion (US$9.6 billion) over the short term. Additionally, CHF 16 billion (US$17.2 billion) of Additional Tier 1 bonds were written down to zero.

Credit Suisse is a globally systemically important bank whose investment banking unit, First Boston, had been recently tarnished by a series of high-profile scandals. The banking crisis in the United States had caused fear among global investors and led to panic over other possibly troubled banks. Credit Suisse's share price plunged after the leading shareholder ruled out further investment into the bank due to regulatory issues. The deal was rapidly agreed upon and announced just before the Asian financial markets opened on Monday morning in order to prevent "market shaking" turmoil in the global financial markets. Soon afterward, central banks across the world announced USD liquidity measures to try and ease wider market panic and avoid a wider banking crisis.
Question: What is the tallest building in the San Francisco Bay Area?
Answer: The tallest building in the SF Bay Area is the Salesforce Tower.
Question: Why did a William the Conqueror, a Frenchman, become the King of England?
Evidence: In the 1050s and early 1060s, William became a contender for the throne of England held by the childless Edward the Confessor, his first cousin once removed. There were other potential claimants, including the powerful English earl Harold Godwinson, whom Edward named as king on his deathbed in January 1066. Arguing that Edward had previously promised the throne to him and that Harold had sworn to support his claim, William built a large fleet and invaded England in September 1066. He decisively defeated and killed Harold at the Battle of Hastings on 14 October 1066. After further military efforts, William was crowned king on Christmas Day, 1066, in London. He made arrangements for the governance of England in early 1067 before returning to Normandy. Several unsuccessful rebellions followed, but William's hold was mostly secure on England by 1075, allowing him to spend the greater part of his reign in continental Europe.
Answer: William the Conqueror was from Normandy, located in northwest France. The King of England in the late 1050s and early 1060s was Edward the Confessor. Edward was William's cousin. Since Edward was childless, there were multiple people who claimed that they were the rightful heir and should become king. These conflicting claims gave rise to armed conflict. William invaded England, where he won the Battle of Hastings, defeating earl Harold Godwinson. A number of battles followed, but William became King of England late in 1066. He dealt with multiple rebellions over the next decade, but retained his power. Ultimately he was able to return to Normandy and rule England from there.
Question: Tell me whether the following are Pokemon or Overwatch characters: Hanzo, Flareon, Mewtwo, Mei, Dratini, Kiriko
Answer: Flareon, Mewtwo, and Dratini are Pokemon. Hanzo, Mei, and Kiriko are Overwatch characters.
Question: Which dataset do they use to build their model?
Evidence: The clinical notes we used for the experiment are provided by domain experts, consisting of 1,160 physician logs of Medical ICU admission requests at a tertiary care center affiliated to Mount Sanai. Prospectively collected over one year, these semi-structured logs contain free-text descriptions of patients' clinical presentations, medical history, and required critical care-level interventions. We identify 818 abbreviations and find 42,506 candidates using domain-specific knowledge (i.e., www.allacronym.com/_medical). The enriched corpus contains 42,506 Wikipedia articles, each of which corresponds to one candidate, 6 research papers and 2 critical care medicine textbooks, besides our raw ICU data.
The clinical notes we used for the experiment are provided by domain experts, consisting of 1,160 physician logs of Medical ICU admission requests at a tertiary care center affiliated to Mount Sanai.
The enriched corpus contains 42,506 Wikipedia articles, each of which corresponds to one candidate, 6 research papers and 2 critical care medicine textbooks, besides our raw ICU data.
Answer: The answers are shown as follows:
* 1,160 physician logs of Medical ICU admission requests
* 42,506 Wikipedia articles
* 6 research papers and 2 critical care medicine textbooks
Question: Write an email to Visa alerting them that I am no longer interested in the position I’m interviewing for since I have accepted another offer. I have a lot of respect for the company and their employee experience is high!
Answer: Thank you so much for this opportunity to continue interviewing! I have really enjoyed getting to know Visa more during this process, but unfortunately must remove myself from the candidate pool at this time. As I shared earlier, I had competing offers with earlier timelines.

This in no way reflects my interest in Visa-- now is such an amazing time to join a function and company in the midst of transformation. It is also so heartening to hear how positive the employee experience is. This is to say that I sincerely hope to stay in touch and that our paths can cross again later down the line.

Thanks again for your coordination!
Question: Write a list of items that are “must buys” at Costco
Answer: 1. Toilet Paper
2. Paper Towels
3 TV’s
4. Jewelry 
5. Water Bottles
6. Any Meat Product
7. Avocados
8. Alcohol
9. Giant Shampoo & Conditioner 
10. Clothes
Question: Does the model proposed by the author having the ability to detect some biases?
Evidence: Conflating hatred content with offensive or harmless language causes online automatic hate speech detection tools to flag user-generated content incorrectly. Not addressing this problem may bring about severe negative consequences for both platforms and users such as decreasement of platforms' reputation or users abandonment. Here, we propose a transfer learning approach advantaging the pre-trained language model BERT to enhance the performance of a hate speech detection system and to generalize it to new datasets. To that end, we introduce new fine-tuning strategies to examine the effect of different layers of BERT in hate speech detection task. The evaluation results indicate that our model outperforms previous works by profiting the syntactical and contextual information embedded in different transformer encoder layers of the BERT model using a CNN-based fine-tuning strategy. Furthermore, examining the results shows the ability of our model to detect some biases in the process of collecting or annotating datasets. It can be a valuable clue in using the pre-trained BERT model to alleviate bias in hate speech datasets in future studies, by investigating a mixture of contextual information embedded in the BERT’s layers and a set of features associated to the different type of biases in data.

Furthermore, examining the results shows the ability of our model to detect some biases in the process of collecting or annotating datasets.
Answer: Yes, it does.
Question: How is the PBMT system trained?
Evidence: Both systems were optimized on the tst2014 using Minimum error rate training BIBREF20 . A detailed description of the systems can be found in BIBREF21 .
Both systems were optimized on the tst2014 using Minimum error rate training BIBREF20 . A detailed description of the systems can be found in BIBREF21 .
Answer: The answers are shown as follows:
* systems were optimized on the tst2014 using Minimum error rate training BIBREF20
Question: Give me a list of things to buy a 12 year old boy
Answer: 1. Vouchers
2. An experience
3. Movie tickets
4. Cash is always king!
Question: Write a review of Neil Gaiman's book American Gods.
Answer: What a phenomenal book. I can see how people would call this a "more mature Percy Jackson", but to me American Gods was much more than just mythology fanfiction. Overall, the imaginative story, noir setting, mysterious plot, witty dialogue, and incredible characters made this one of the best books I've read this year.

Starting with the setting and premise - gods in the modern world has become a setting of it's own. Most notably, this story reminds me of a western version of Noragami, where a god's strength stems from their worshipers. It's hilarious to see deities of old living mundane lives, frankly quite charming. Our characters navigate through a spooky setting, but it's never overbearing nor depressing.

But what really makes this book special are the characters and dialogue. Shadow and Wednesday are an amazing duo; between Shadows quiet reflections and Wednesday's blunt terrorizing, the pair travel across rural America, running through a plethora of interesting icons and people.
Question: Where should I go this summer?
Answer: It depends, for many people, a summer destination is all about going to a nice beach, enjoying the sunshine and relaxing. For others summer vacation is about going on a new adventure to explore a nice country, city or a cool nearby village. 
Here are some ideas for a summer vacation if you are interested in traveling to Europe
Road trip across the Amalfi coast for one week. 
Cruising around the Croatian islands. 
Ancient history tour in Rome, Vatican City & Athens.
Enjoy the beautiful beaches in Southern France. 
There are many other beautiful places to visit but this will depend on your budget, duration and your interests.
Question: what classifiers were used in this paper?
Evidence: We feed the above-described hand-crafted features together with the task-specific embeddings learned by the deep neural neural network (a total of 1,892 attributes combined) into a Support Vector Machines (SVM) classifier BIBREF37 . SVMs have proven to perform well in different classification settings, including in the case of small and noisy datasets.
We feed the above-described hand-crafted features together with the task-specific embeddings learned by the deep neural neural network (a total of 1,892 attributes combined) into a Support Vector Machines (SVM) classifier BIBREF37 .
Answer: The answers are shown as follows:
* Support Vector Machines (SVM) classifier
Question: What are tacos?
Answer: Tacos are Mexican food, made up of a tortilla with a stuffing of protein (meats) or veggies. You add toppings like cilantro, onions, and hot sauce to the tacos. Tacos are delicious and make a fabulous meal.
Question: How many people were present in West Berlin when US President JFK delivered his infamous "Ich bin ein Berliner" speech?
Answer: Approximately one million people were in attendance on June 26, 1963.
Question: What is recency bias?
Answer: Recency bias is the overweighting the result of more recent events when predicting what will happen in the future.  For example, if I recently experienced a pandemic that dramatically affected my quality of life, I may tend to overestimate the likelihood of another pandemic in the near future.
Question: Give me 5 ways to relax for an hour ?
Answer: Here are a few suggestions
1. Go for a walk outside
2. Catch up on sleep 
3. Read a book
4. Watch Netflix
5. Call a friend
Question: Why are Dr. Seuss books so good?
Answer: Dr. Suess books are written in a different style from traditional books.  They are written with a play on words, have made up words that are tongue twisters, and use carefully crafted silly rhyming and poetry to make the reading fun.  Some of the most famous Dr. Seuss books are Green Eggs and Ham, Cat in in the Hat, and How the Grinch Stole Christmas.  An example of the poetry and rhyming from a Dr Seuss book is "one fish, two fish, red fish, blue fish" and "look at me, look at me, look at me now, its fun to have fun, but you have to know how."
Question: What is the strength of Cost-sensitive classification in model training?
Evidence: Cost-sensitive classification can be used when the “cost” of mislabelling one class is higher than that of mislabelling other classes BIBREF9, BIBREF10. For example, the real cost to a bank of miscategorising a large fraudulent transaction as authentic is potentially higher than miscategorising (perhaps only temporarily) a valid transaction as fraudulent. Cost-sensitive learning tackles the issue of class imbalance by changing the cost function of the model such that misclassification of training examples from the minority class carries more weight and is thus more `expensive'. This is achieved by simply multiplying the loss of each example by a certain factor. This cost-sensitive learning technique takes misclassification costs into account during model training, and does not modify the imbalanced data distribution directly.
Cost-sensitive learning tackles the issue of class imbalance by changing the cost function of the model such that misclassification of training examples from the minority class carries more weight and is thus more ‘expensive'. This is achieved by simply multiplying the loss of each example by a certain factor. This cost-sensitive learning technique takes misclassification costs into account during model training, and does not modify the imbalanced data distribution directly.
Answer: It reduces the influence of class imbalance by taking misclassification costs into account , and it does not modify the imbalanced data distribution directly.
Question: How many dwarf planets are there in our solar system?
Answer: Currently only 5 objects are officially recognized as dwarf planets in our solar system. These are named as Ceres, Pluto, Eris, Haumea, and Makemake.
Question: Give me 5 examples of why using a prime lens is better than a zoom lens for photography ?
Answer: -Better  low light photography even without a flash
-Prime lenses have fewer moving parts 
-Better performance 
-Sharper Images 
-High chances of getting  Bokeh
Question: What are the child tasks in the experiment?
Evidence: In this section, we describe the languages experimented with, datasets used, the network hyper-parameters used in our experiments.
Bengali, Gujarati, Marathi, Malayalam and Tamil are the source languages, and translation from these to Hindi constitute the child tasks.
Answer: Bengali, Gujarati, Marathi, Malayalam and Tamil are the source languages, and translation from these to Hindi constitute the child tasks.
Question: What are some quick ways to lose all of my money?
Answer: Here are some quick ways to lose all of your money:
1. Place all of your money on red at the roulette table.
2. Play high-stakes blackjack everyday for the next week.
3. Buy random crypto currencies like Solana.
4. Buy extremely out of the money options on trading applications like Robinhood.
5. Loan it to friends and families with a history of not paying you back.
Question: Write a bullet-pointed list of updates from a college club fundraising team lead about their fundraising work from last week.
Answer: * Planned fundraising efforts for the next week, as well as implemented donut sales on campus to increase fundraising streams.
* Sent out Google Form to gauged interest of the club on buying club-branded shirts and stickers. By mid-week, we will make final decisions on apparel and begin sending out order forms.
* Continued with burger and chicken wings food sales on the central campus plaza.
Question: Who composed the 'Moonlight Sonata', and when?
Answer: Commonly known as the Moonlight Sonata, the Piano Sonata No. 14 in C-sharp minor "Quasi una fantasia", Op. 27, No. 2, was composed by Ludwig van Beethoven.
The composition was completed in 1801 and dedicated to the Countess Giulietta Guicciardi in 1802. It's one of the most popular musical compositions for the piano.
Question: How are the teams which qualify for the National Football League Playoffs determined?
Answer: The 32 teams that comprise the National Football League are organized by two conferences, the American and National, with four divisions of four teams in each conference.  Each year the team with the best record in their division automatically qualifies for the playoffs.  In addition, the three remaining teams with the best records in each conference also qualify and are designated as "wildcards".  Tiebreakers are used to determine who makes the playoffs in scenarios where two or more teams finish with the same number of wins.  Tiebreakers can include head-to-head competition, record in conference, and record against common opponents.
Question: What else is tried to be solved other than 12 tenses, model verbs and negative form?
Evidence: Moreover, this work also handles the cases of singular/plural, subject pronoun/object pronoun, etc. For instance, the pronoun “he" is used for the subject as “he" but is used for the object as “him".
Moreover, this work also handles the cases of singular/plural, subject pronoun/object pronoun, etc. For instance, the pronoun “he" is used for the subject as “he" but is used for the object as “him".
Answer: The answers are shown as follows:
* cases of singular/plural, subject pronoun/object pronoun, etc.
Question: Can I provide commercial software or services based on Spark?
Answer: Yes, as long as you respect the Apache Software Foundation's software license and trademark policy. In particular, note that there are strong restrictions about how third-party products use the "Spark" name (names based on Spark are generally not allowed). Please also refer to our trademark policy summary.
Question: What kind of food comprises Estonian cuisine?
Evidence: Traditional Estonian cuisine has substantially been based on meat and potatoes, and on fish in coastal and lakeside areas, but now bears influence from many other cuisines, including a variety of international foods and dishes, with a number of contributions from the traditions of nearby countries. Scandinavian, German, Russian, Latvian, Lithuanian and other influences have played their part. The most typical foods in Estonia have been rye bread, pork, potatoes and dairy products. Estonian eating habits have historically been closely linked to the seasons. In terms of staples, Estonia belongs firmly to the beer, vodka, rye bread and pork "belt" of Europe.
Answer: Estonian cuisine is generally based on meat, potatoes, fish, and more recently bears.  In most typical Estonian foods you'll find rye bread, pork, potatoes, and dairy products.
Question: What dataset do they use?
Evidence: SMT techniques require a parallel corpus in thr source and thr target language. A text-code parallel corpus similar to Fig. FIGREF12 is used in training. This parallel corpus has 18805 aligned data in it . In source data, the expression of each line code is written in the English language. In target data, the code is written in Python programming language.
SMT techniques require a parallel corpus in thr source and thr target language. A text-code parallel corpus similar to Fig. FIGREF12 is used in training. This parallel corpus has 18805 aligned data in it . In source data, the expression of each line code is written in the English language. In target data, the code is written in Python programming language.
Answer: A parallel corpus where the source is an English expression of code and the target is Python code.
Question: What was the first name of Thomas Attewell's brother and cousin?
Evidence: Thomas Attewell (7 November 1869 – 6 July 1937) was an English first-class cricketer. Attewell was a right-handed batsman who bowled right-arm medium pace. He was born at Keyworth, Nottinghamshire.

His brother William played first-class cricket for Nottinghamshire and the Marylebone Cricket Club, as well as Test cricket for England. His cousin Walter Attewell played first-class cricket for Nottinghamshire.
Answer: William and Walter
Question: What are cons of getting a dog?
Answer: 1. It is hard to make long travel plans while owning a dog.
2. Depending on the breed seasonal shedding could be a problem.
3. Responsible ownership of a dog is a big financial investments.
4. Dogs live shorter lives than humans so upcoming emotional toll could be a detractor.