DataHammer/scimrc huggingface dataset:
Question: From this passage, tell me what was the highest grossing movie in 2022 and what was the second highest grossing movie?
Evidence: Avatar: The Way of Water became the 51st film to gross $ 1 billion worldwide, the sixth film to gross $2 billion worldwide, the sixth-fastest film to cross the billion-dollar mark at 14 days, the second-fastest to gross the $2 billion mark, the highest grossing film of 2022, and the highest-grossing film of the COVID-19 pandemic era.
It had the 11th-biggest global opening of all time and the third-biggest global opening for a film in the pandemic era behind Spider-Man: No Way Home and Doctor Strange in the Multiverse of Madness, earning $441.7 million in its first weekend.
It also achieved the second-highest global opening weekend ever for a film released in IMAX cinemas with $48.8 million.
With the release of Avatar: The Way of Water, Walt Disney Studios Motion Pictures led over other film distributors in worldwide box office grosses and crossed the $4.9 billion mark for the eighth year. Disney’s cumulative gross was generated from 16 film releases across its various studio divisions.
Top Gun: Maverick became the 49th film to gross $1 billion worldwide.
Additionally, the film surpassed Mission: Impossible – Fallout (2018) to become Tom Cruise's highest-grossing film of all time at the worldwide box office and also surpassed War of the Worlds (2005) to become Cruise's highest-grossing film at the domestic box office.
It also passed The Mummy (2017) as Cruise's biggest opening weekend at the worldwide box office and also passed War of the Worlds (2005) as Cruise's biggest opening at the domestic box office and his first film to open to over $100 million in the US.
It also passed Pirates of the Caribbean: At World's End (2007), another Jerry Bruckheimer produced movie, to have the highest Memorial Day opening weekend and passed Shrek 2 (2004) to have the lowest second-weekend drop for a movie that made over $100M in its opening weekend.
The film surpassed Transformers: Dark of the Moon (2011) to become the highest-grossing film distributed solely by Paramount Pictures worldwide, and Titanic (1997) to become Paramount's highest grossing film in the United States and Canada.
Answer: The highest grossing movie in 2022 is Avatar The way of Water, which grossed $2B worldwide. I unfortunately cannot tell what was the second highest grossing movie as that information is not available in the passage you shared with me
Question: Have any Defensive players won the Heisman Trophy?
Answer: Charles Woodson is the only Heisman Trophy Winner who was primarily a defensive player.
Question: Classify each of the following as safe or unsafe to eat for a human: hamburger, metal plate, iPhone, onion, tree, potato chip, candle, ice cream, backpack, sweater, boiled egg.
Answer: Safe to eat: hamburger, onion, potato chip, ice cream, boiled egg
Unsafe to eat: metal plate, iPhone, tree, candle, backpack, sweater
Question: Does this approach perform better than context-based word embeddings?
Evidence: To verify the word embeddings learned by our model we use the task of synonym discovery, whereby we analyze if it is possible to identify a pair of words as synonyms only through their embedding vectors. Synonym discovery is a common task in research; and it has been used before to test word embedding schemes BIBREF0 . We compare the performance of our Chinese word embedding vectors in the task of synonym discovery against another set of embedding vectors that was constructed with a co-occurrence model BIBREF1 . We also investigate the performance of synonym discovery with the Sino-Korean word embeddings by our method. Our test results shows that our approach out-performs the previous model.
Our embeddings also proved to perform better than our benchmark dataset. Figure shows the distribution of the similarity measure between pairs of synonyms and random pairs of words in the benchmark dataset. In this sample, almost 32% of synonyms show a similarity score that places them away from zero, while 5% of random pairs of words are placed outside of that range. Table compares performance, and dimensionality in both strategies to learn embeddings.
We compare the performance of our Chinese word embedding vectors in the task of synonym discovery against another set of embedding vectors that was constructed with a co-occurrence model BIBREF1 .
Our embeddings also proved to perform better than our benchmark dataset.
Answer: Yes.
Question: Which of the following are names typically given to girls, typically given to boys, or names that could easily be given to either a boy or a girl: Sam, Bill, Liz, Tracy, Mary, Joe, Taylor, Missy, Ralph, Scott, Michelle, Michael, Frank, Cheryl, Ryan, Stephenie.
Answer: Of these, Bill, Joe, Ralph, Scott, Michael, Frank and Ryan are names that would typically be for boys; Liz, Mary, Missy, Michelle, Cheryl and Stephenie are names that would typically be for girls; and Sam, Tracy, and Taylor are names that could apply to either a girl or a boy.
Question: What was the SS Robert Coryndon?
Evidence: SS Robert Coryndon was a British twin-screw passenger and cargo ferry on Lake Albert in central Africa.

She was built in England in 1929 and reassembled in kit form at Lake Albert in 1930. She ran aground in 1962 and lay derelict until she was broken up for scrap between 2009 and 2012.

John I. Thornycroft & Company at Woolston, Hampshire built the ship for Kenya and Uganda Railways and Harbours in 1929–30. She was named after the South African Sir Robert Coryndon, who was Governor of Uganda 1918–22.

She was a "knock-down" ship. She was assembled in 1929 at Woolston. All her parts were marked with numbers, she was disassembled into many hundreds of parts, and transported in kit form to Africa, where she was reassembled on the shore of Lake Albert in 1930. Part of the overland journey to Lake Albert was by lorry, which severely limited the maximum size and weight of her parts.

Robert Coryndon was part of a plan for a network of railway, river steamer and lake steamer services linking British interests in Egypt, East Africa and southern Africa. Sir Winston Churchill described her as "the best library afloat".

Fate
Robert Coryndon sank in 1962, around the time of Ugandan independence from Britain. She was not refloated.

In 1967 the East African Railways and Harbours Corporation (EAR&H) offered her wreck for sale, but she remained largely intact in 2009.

By the beginning of 2012 her wreck had been taken away "in bits and pieces by cutting all the metal remains for scrap" and only her aft king posts were still visible above the water.
Answer: The SS Coryndon was a passenger and cargo ferry on Lake Albert in central Africa. It was built in 1929-30 and named after Sir Robert Coryndon, who was Governor of Uganda from 1918-22. It sank in 1962 and has been nearly entirely salvaged for scrap as of 2012.
Question: What is concept-map-based MDS?
Evidence: Concept-map-based MDS is defined as follows: Given a set of related documents, create a concept map that represents its most important content, satisfies a specified size limit and is connected.
We define a concept map as a labeled graph showing concepts as nodes and relationships between them as edges. Labels are arbitrary sequences of tokens taken from the documents, making the summarization task extractive. A concept can be an entity, abstract idea, event or activity, designated by its unique label. Good maps should be propositionally coherent, meaning that every relation together with the two connected concepts form a meaningful proposition.
The task is complex, consisting of several interdependent subtasks. One has to extract appropriate labels for concepts and relations and recognize different expressions that refer to the same concept across multiple documents. Further, one has to select the most important concepts and relations for the summary and finally organize them in a graph satisfying the connectedness and size constraints.
Concept-map-based MDS is defined as follows: Given a set of related documents, create a concept map that represents its most important content, satisfies a specified size limit and is connected. We define a concept map as a labeled graph showing concepts as nodes and relationships between them as edges. Labels are arbitrary sequences of tokens taken from the documents, making the summarization task extractive. A concept can be an entity, abstract idea, event or activity, designated by its unique label. Good maps should be propositionally coherent, meaning that every relation together with the two connected concepts form a meaningful proposition.
Answer: Given a set of related documents, create a concept map that represents its most important content, satisfies a specified size limit and is connected. They define a concept map as a labeled graph showing concepts as nodes and relationships between them as edges. Labels are arbitrary sequences of tokens taken from the documents, making the summarization task extractive. A concept can be an entity, abstract idea, event or activity, designated by its unique label. Good maps should be propositionally coherent, meaning that every relation together with the two connected concepts form a meaningful proposition.
Question: Who is Paul Cezanne?
Evidence: Paul Cézanne (/seɪˈzæn/ say-ZAN, also UK: /sɪˈzæn/ sə-ZAN, US: /seɪˈzɑːn/ say-ZAHN; French: [pɔl sezan]; 19 January 1839 – 22 October 1906) was a French artist and Post-Impressionist painter whose work introduced new modes of representation and influenced avant garde artistic movements of the early 20th century. Cézanne is said to have formed the bridge between late 19th-century Impressionism and the early 20th century's new line of artistic enquiry, Cubism.
Answer: Paul Cezanne was a French artist who introduced new modes of representation such as cubism in the early 20th century.
Question: I'm going on a hike and the weather is cold, how should I dress?
Answer: When hiking, it is important to dress in layers. As you hike, your body will heat up, and you will want the flexibility to remove layers accordingly. They layers should consist of a base layer to wick away sweat, an insulating layer to help retain body heat, and an outer layer to shield from rain or wind. You should also consider weather like snow or rain as this may change what you need to bring.
Question: Who is the best golfer to ever play the game?
Answer: Tiger Woods is the best golfer ever for several reasons. He set or broke most major records in the history of the PGA tour. He was named Player of the Year ten times and was the fifth player to ever win a career grand slam which he accomplished at the age of 24. He has won each major at least three times. There hasn't been a golfer that has been more dominant across every major category for as long as Tiger Woods was.
Question: Where did Riley Redgate sarted her first novel?
Evidence: Robinson was raised in Winston-Salem, North Carolina. She attended Richard J. Reynolds High School, where she began her first novel, Seven Ways We Lie. She is an alumna of Kenyon College in Gambier, Ohio, where she majored in economics, graduating in 2016. Her debut novel was published before she graduated. While at Kenyon, Robinson won the college's James E. Michael Playwriting Award for her play Mourning Sickness.

Robinson worked from Chicago as writing apprentice for the satirical media outlet The Onion. Her three novels are Seven Ways We Lie (2016), Note Worthy (2017), and Final Draft (2018), all published by Amulet, an imprint of Abrams Books.

Robinson is bisexual, of half-Irish and half-Chinese descent, and the characters in her novels similarly lie "in the middle of a spectrum rather than out at the ends".
Answer: Riley Redgate started her first novel while attending Richard J. Reynolds High School.
Question: Does the combination of neural network and Bayesian model (SVAE) yield a significant improvement in the AUD in terms of consistency?
Evidence: We have conducted an analysis of the state-of-the-art Bayesian approach for acoustic unit discovery on a real case of low-resource language. This analysis was focused on the quality of the discovered units compared to the gold standard phone alignments. Outcomes of the analysis are i) the combination of neural network and Bayesian model (SVAE) yields a significant improvement in the AUD in term of consistency ii) Bayesian models can naturally embed information from a resourceful language and consequently improve the consistency of the discovered units. Finally, we hope this work can serve as a baseline for future research on unsupervised acoustic unit discovery in very low resource scenarios.
Outcomes of the analysis are i) the combination of neural network and Bayesian model (SVAE) yields a significant improvement in the AUD in term of consistency ii) Bayesian models can naturally embed information from a resourceful language and consequently improve the consistency of the discovered units.
Answer: Yes, it does.
Question: Give me two examples of an Act of independent significance. Separate them in a list.
Evidence: The doctrine of acts of independent significance at common law permits a testator to effectively change the disposition of his property without changing a will, if acts or events changing the disposition have some significance beyond avoiding the requirements of the will.

The doctrine is frequently applied under the following two circumstances:

    The testator devises assets to a class of beneficiaries where the testator controls membership. For example, Joey leaves the contents of his bank account "to my employees." If Joey then fires some of old employees and hires new ones, the new employees will inherit the contents of the bank account under this provision.
    The testator devises a general type of property, and then changes the specific items of property within that category. For example, Joey writes in his will, "I leave my car to Rachel". Joey drives a 1974 AMC Gremlin at the time of the testamentary instrument, but later sells the Gremlin and purchases a 2016 Rolls-Royce Phantom Drophead Coupé with suicide doors and teak paneling. Because Joey bought a new car to get a more comfortable ride, rather than to change a will without going through the testamentary formalities, the gift to Rachel remains enforceable.
Answer: - Joey leaves the contents of his bank account "to my employees." If Joey then fires some of the old employees and hires new ones, the new employees will inherit the contents of the bank account under this provision.

- Joey writes in his will, "I leave my car to Rachel". Joey drives an old car at the time of the testamentary instrument, but later sells the Gremlin and purchases a new car. Because Joey bought a new car to get a more comfortable ride, rather than to change a will without going through the testamentary formalities, the gift to Rachel remains enforceable.
Question: Classify the following information as 'PII' or 'not PII' : Social Security Number, Home Address, Age, Number of Employees, City Population, Gender, Business Phone
Answer: Social Security Number - PII
Home Address - PII 
Age - PII
Number of Employees - Not PII
City Population - Not PII
Gender - Not PII 
Business Phone - Not PII
Question: What languages are were included in the dataset of hateful content?
Evidence: As previously mentioned, there is no German hate speech corpus available for our needs, especially not for the very recent topic of the refugee crisis in Europe. We therefore had to compile our own corpus. We used Twitter as a source as it offers recent comments on current events. In our study we only considered the textual content of tweets that contain certain keywords, ignoring those that contain pictures or links. This section provides a detailed description of the approach we used to select the tweets and subsequently annotate them.
As previously mentioned, there is no German hate speech corpus available for our needs, especially not for the very recent topic of the refugee crisis in Europe. We therefore had to compile our own corpus.
Answer: The answers are shown as follows:
* German
Question: Who is Evelyn Quan Wang in the move "Everything Everywhere All at Once"?
Evidence: Evelyn Quan Wang is a middle-aged Chinese American immigrant who runs a laundromat with her husband, Waymond; two decades earlier, they eloped to the United States and had a daughter, Joy. The laundromat is being audited by the Internal Revenue Service (IRS), Waymond is trying to serve Evelyn divorce papers in an attempt to get her attention so they can talk things out regarding their marriage, Evelyn's demanding father (referred to as Gong Gong, Cantonese for 'grandfather') is visiting for her Chinese New Year party, and Evelyn is reluctant to accept Joy's lesbian relationship with her non-Chinese girlfriend Becky (only introducing Becky to Gong Gong as Joy's "very good friend").
Answer: Evelyn Quan Wang is a middle-aged Chinese American immigrant who runs a laundromat with her husband, Waymond.
Question: What are some best practices to keep car tires from losing tread prematurely
Answer: To keep car tires from losing tread prematurely follow these best practices
1) Ensure the tire pressure is always at the car and tire manufacturers recommended PSI levels
2) Ensure you rotate tires every 6 months
3) Enhance your sense of breaking scenarios and try to gently break into it rather than abruptly slamming the breaks
4) Similarly try to accelerate gently as you start your drive rather than accelerating at a high rate.
Question: How much sleep is too much?
Answer: You can get as much sleep as you want. 7-8 hours is considered normal for adults. But everyone is different, some enjoy taking naps whenever available for an energy boost or just to get relaxed. You might suffer from narcolepsy if you fall asleep without warning anytime or anywhere. Go see a doctor in that case.
Question: Given this paragraph, what method of scientific study did Edmund Selous champion?
Evidence: Edmund Selous started as a conventional naturalist, but developed a hatred of the killing of animals for scientific study and was a pioneer of bird-watching as a method of scientific study. He was a strong proponent of non-destructive bird-study as opposed to the collection of skins and eggs.
Answer: Edmund Selous was a pioneer of bird-watching as a method of scientific study.
Question: Can you tell me about Tabarra?
Evidence: Tabarra agitation of 1939 was an event when some 18,000 Shias were jailed during months of March, April, and May 1939 in Lucknow, India.

A civil disobedience movement was at once started by Shias following the Congress Government communique of 31 March 1939 (which allowed reciting of previously banned Madhe-Sahaba at public meetings). Sunnis called off their civil disobedience movement but its effect on Shias was far greater than anticipated; they had the authority of two committees (Piggot committee and Allsop committee) and the practice of thirty years in support of their position. Some 1800 Shias courted arrest, including prominent Shia figures such as Syed Ali Zaheer (newly elected MLA from Allahabad-Jaunpur), the Princes of the former royal family of Awadh, Sayed Muhammad Naseer Naseer-ul-Millat the son of Maulana Nasir a respected Shia mujtahid (the eldest son, student and designated successor of Maulana Sayed Nasir Hussain of Abaqati family), Maulana Sayed Kalb-e-Husain and his son Maulana Kalb-e-Abid (both ulema of Nasirabadi family) and the brothers of Raja of Salempur and the Raja of Pirpur, important ML leaders. It was believed that Maulana Nasir himself besides the top ranking ML leaders such as Raja of Mahmudabad and Raja of Pirpur would together court arrest. Maulana Azad, appointed an arbitrator by the parties, called a conference of Shias and Sunnis, but it failed to produce a settlement. Azad conveyed to Sir Haig, the Governor, his view that the communique was 'based on inadequate appreciation of the situation and, therefore, an error of judgement'. But, this statement came just a day before the Barawafat, and a Madhe-Sahaba procession was taken out. The Shias too were allowed a counter-procession, it was disturbed and resulted in a serious riot. Several people died and police had to open fire several times. The following year i.e. 1940, the district authorities banned the public recitation of Madhe-Sahaba and Tabarra in processions and meetings held in public places.
Answer: Civil disobedient movement in 1939 is an event that is called Tabarra agitation. Around 18,000 Shias were jailed during 1939 in Lucknow, India
Question: What are some of the causes for the 1929 US stock market crash?
Answer: The 1920’s were a booming time for Americans as the stock market was surging due to speculative investing.  Stock prices rose to records heights which drove the public to invest their liquid assets into securities.  Billions of dollars were drawn from banks for broker’s loans to carry margin accounts.  People were mortgaging their homes to pour money into stocks.  In late 1929, the market eventually overheated and prices began to fall despite efforts by the banks to buy up large blocks of stock to stem the losses.  Eventually, the panic was too much and the market crashed on Black Monday, October 24th when the market closed down 12.8 percent.  The sharp decline in the 1929 stock market eventually led to the Great Depression of the 1930’s.
Question: What is the length of the song "The New Deal"?
Evidence: Side A
1. "H2O Gate Blues" – 7:58 (about the Watergate break-in and cover-up) (from Winter in America)
2. "We Beg Your Pardon (Pardon our Analysis)" – 7:52 (about the pardon of Richard Nixon) (from The First Minute of a New Day)
3. "The New Deal" – 3:10
Side B
4. "Jose Campos Torres" – 2:36 (about Jose Campos Torres, a U.S. Army veteran who was arrested and then murdered and tossed into a bayou by two police officers in Houston in 1978, spurring the Moody Park Riot)
5. "The Ghetto Code (Dot Dot Dit Dit Dot Dot Dash)" – 12:57
6. "Bicentennial Blues" – 8:39 (from It's Your World)
Answer: 3:10
Question: Which sports would be easiest to find success in if you’re not tall: baseball, soccer, basketball, bowling.
Answer: Soccer and bowling would be the two easiest sports in this list to succeed in if you’re not tall.
Question: Do they propose a new model to better detect Arabic bots specifically?
Evidence: In this work, we build a novel regression model, based on linguistic, content, behavioral and topic features to detect Arabic Twitter bots to understand the impact of bots in spreading religious hatred in Arabic Twitter space. In particular, we quantitatively code and analyze a representative sample of 450 accounts disseminating hate speech from the dataset constructed in our previous work BIBREF18 , BIBREF19 for bot-like behavior. We compare our assigned bot-likelihood scores to those of Botometer BIBREF14 , a well-known machine-learning-based bot detection tool, and we show that Botometer performs a little above average in detecting Arabic bots. Based on our analysis, we build a predictive regression model and train it on various sets of features and show that our regression model outperforms Botometer's by a significant margin (31 points in Spearman's rho). Finally, we provide a large-scale analysis of predictive features that distinguish bots from humans in terms of characteristics and behaviors within the context of social media.
In this work, we build a novel regression model, based on linguistic, content, behavioral and topic features to detect Arabic Twitter bots to understand the impact of bots in spreading religious hatred in Arabic Twitter space. 
Answer: Yes.