DataHammer/scimrc huggingface dataset:
Question: What is the conclusion of this paper?
Evidence: In summary, we conducted two feature study experiments to assess the contribution of feature groups and to determine the optimal percentile of top ranked features for classifying Twitter tweets in the depression schema hierarchy. From these experiments, we conclude that simple lexical features and reduced feature sets can produce comparable results to the much larger feature dataset.
From these experiments, we conclude that simple lexical features and reduced feature sets can produce comparable results to the much larger feature dataset.
Answer: From these experiments, they conclude that simple lexical features and reduced feature sets can produce comparable results to the much larger feature dataset.
Question: Where is Salvador Brazil?
Answer: Salvador is a Brazilian municipality and capital city of the state of Bahia. Situated in the Zona da Mata in the Northeast Region of Brazil, Salvador is recognized throughout the country and internationally for its cuisine, music and architecture. The African influence in many cultural aspects of the city makes it a center of Afro-Brazilian culture. As the first capital of Colonial Brazil, the city is one of the oldest in the Americas and one of the first planned cities in the world, having been established during the Renaissance period. Its foundation in 1549 by Tomé de Sousa took place on account of the implementation of the General Government of Brazil by the Portuguese Empire.
Question: Give me a list of Premier League winners in the last 5 years with corresponding points.
Answer: 2021-2022: Manchester City, 93
2020-2021: Manchester City, 86
2019-2020: Liverpool, 99
2018-2019: Manchester City, 98
2017-2018: Manchester City, 100
Question: How is Tesla's approach to full autonomy is different from the other companies?
Evidence: Tesla's approach to achieve full autonomy is different from that of other companies. Whereas Waymo, Cruise, and other companies are relying on highly detailed (centimeter-scale) three-dimensional maps, lidar, and cameras, as well as radar and ultrasonic sensors in their autonomous vehicles, Tesla's approach is to use coarse-grained two-dimensional maps and cameras (no lidar) as well as radar and ultrasonic sensors. Tesla claims that although its approach is much more difficult, it will ultimately be more useful, because its vehicles will be able to self-drive without geofencing concerns. Tesla's self-driving software has been trained on over 20 billion miles driven by Tesla vehicles as of January 2021. Tesla also designed a self-driving computer chip that has been installed in its cars since March 2019.
Answer: Tesla uses e coarse-grained two-dimensional maps and cameras (no lidar) as well as radar and ultrasonic sensors whereas its competitors rely on highly detailed  (centimeter-scale) three-dimensional maps, lidar, and cameras
Question: If you could come back to life as any person, animal or thing, what or who would you be and how would you live your second life?
Answer: If I were to come back to life as anything, I would love to come back as a dog. Ideally, I would be with a loving family since from my early years as a puppy and be their guard dog. I would ensure that they would be loved, cuddled and cared for every day. Many times they will have to pick up after me because as a puppy I won't know any better and I need them to teach me all the things I need to know. Over the years, I will get to enjoy going on walks to the park, lay on the couch, do tricks for treats and play with my humans. My goal would be to ensure that everyone around me knows that they are loved by me. This world needs more kind souls and love and that's why I would come back as a dog.
Question: Does their model have highway layers?
Evidence: The architecture of our proposed model is as shown in Fig. FIGREF3 . It looks similar to the character-aware neural language model proposed by BIBREF1 , but we represent a word by the sequence of radical embeddings instead of character embeddings. Besides, unlike the former model, there are no highway layers in the proposed model, because we find that highway layers do not bring significant improvements to our proposed model (see Section SECREF31 ).
Besides, unlike the former model, there are no highway layers in the proposed model, because we find that highway layers do not bring significant improvements to our proposed model (see Section 5.3).
Answer: No.
Question: How many label options are there in the multi-label task?
Evidence: For the sentiment analysis, we look at our problem in a multi-label setting, our two labels being sentiment polarity and the candidate/category in consideration. We test both single-label classifiers and multi-label ones on the problem and as intuition suggests, the multi-label classifier RaKel performs better. A combination of document-embedding features BIBREF3 and topic features (essentially the document-topic probabilities) BIBREF4 is shown to give the best results. These features make sense intuitively because the document-embedding features take context of the text into account, which is important for sentiment polarity classification, and topic features take into account the topic of the tweet (who/what is it about).
For the sentiment analysis, we look at our problem in a multi-label setting, our two labels being sentiment polarity and the candidate/category in consideration.
Answer: The answers are shown as follows:
*  two labels
Question: What is a economic trait of Generation Z (Gen Z)?
Evidence: As consumers, members of Generation Z are typically reliant to the Internet to research their options and to place orders. They tend to be skeptical and will shun firms whose actions and values are contradictory. Their purchases are heavily influenced by trends they see on social media.

In the West, while majorities might signal their support for certain ideals such as "environmental consciousness" to pollsters, actual purchases do not reflect their stated views, as can be seen from their high demand for cheap but not durable clothing ("fast fashion"), or preference for rapid delivery. Moreover, young Western consumers of this cohort are less likely to pay a premium for what they want compared to their counterparts from emerging economies.
Answer: Gen Z are dependent on the internet to do research and also to place orders. They do not use purchases to signal morals or views, as they tend to purchase fast fashion and prefer fast delivery over quality.
Question: What are the different types of fees that are charged in the US National Park?
Answer: Experiencing a US National park to it's fullest may require different kinds of fees and charges. The entree fee to the park, can vary based on vehicle and visitor type, and also can be different across parks. If one has plans of visiting multiple national parks/preserves within 12 months, the national park pass can be a good purchase. Many national parks offer activities within the facilities with an extra fee. Some of the parks are equipped with restaurants and lodges for a proper meal or stay, and the fees are charged accordingly. Most of the parks, if not all would have convenience store in / attached / near to the visitor center, which can offer frozen meals and other merchandizes for a cost.
Question: why are lot of the women more structured and methodical in work, compared to men
Answer: many studies have been conducted to support that women have better organisational skills then men. This trait is also evident outside workplaces at home where women are generally the ones who organise things at home compared to their male counterpart. Organising and being methodical helps in being efficient and do multi tasking better. As more and more women are entering workforce, they continue to take the bigger share of the responsibility of home weather it child care, or home maintenance. In order to manage these women generally spend their time planning and organising things and executing the plan which helps them multi task. This is also the reason why women tend to clock required work hours as they have responsibilities outside work as well, so they have to be efficient in getting things done in 8 hours which men are generally more free to take longer hours to complete.
Question: Which is longest road or highway or motorway in the world
Evidence: This article lists the world's longest road routes that are either officially numbered or otherwise known under a single name. Some of the roads may still be partially planned or under construction.

Pan-American Highway	30,000 km (19,000 mi)	Americas	Prudhoe Bay, Alaska, United States United States	Puerto Montt or Quellón, Chile Chile or Ushuaia, Argentina Argentina	Longest road according to the Guinness Book of Records.
Incomplete at the Darién Gap, causing the northern and southern segments to be actually long about 11,500 and 9,600 km.
Answer: the longest road in the world is in Americas. The longest road is a highway called Pan American highway. It spans 30000 Kilometers or 19000 miles. It starts from Prudhoe Bay, Alaska in United states and ends at Puerto Montt or Quellón, Chile Chile or Ushuaia, Argentina Argentina

The pan american highway is registered as longest road in the world in guiness book of world records 

There are also other categories of longest road in the worlds like Asian highway which starts in Kapıkule, Turkey and ends in Tokyo, Japan. Asian highway is longest uninterrupted highway in the world. Length of the asian highway is 20557 Kilometers or 12774 miles

Longest road within the single country is in Australia. The name of the road is Highway 1. This is loop road and legnth of the highway is 14500 Kilometers or 9000 miles
Question: What is the new dataset created by the authors?
Evidence: We created a new dataset called CW-USPD-2016 (check-worthiness in the US presidential debates 2016) for finding check-worthy claims in context. In particular, we used four transcripts of the 2016 US election: one vice-presidential and three presidential debates. For each debate, we used the publicly-available manual analysis about it from nine reputable fact-checking sources, as shown in Table TABREF7. This could include not just a statement about factuality, but any free text that journalists decided to add, e.g., links to biographies or behavioral analysis of the opponents and moderators. We converted this to binary annotation about whether a particular sentence was annotated for factuality by a given source. Whenever one or more annotations were about part of a sentence, we selected the entire sentence, and when an annotation spanned over multiple sentences, we selected each of them.
Ultimately, we ended up with a dataset of four debates, with a total of 5,415 sentences. The agreement between the sources was low as Table TABREF8 shows: only one sentence was selected by all nine sources, 57 sentences by at least five, 197 by at least three, 388 by at least two, and 880 by at least one. The reason for this is that the different media aimed at annotating sentences according to their own editorial line, rather than trying to be exhaustive in any way. This suggests that the task of predicting which sentence would contain check-worthy claims will be challenging. Thus, below we focus on a ranking task rather than on absolute predictions. Moreover, we predict which sentence would be selected (i) by at least one of the media, or (ii) by a specific medium.
Note that the investigative journalists did not select the check-worthy claims in isolation. Our analysis shows that these include claims that were highly disputed during the debate, that were relevant to the topic introduced by the moderator, etc. We will make use of these contextual dependencies below, which is something that was not previously tried in related work.
We created a new dataset called CW-USPD-2016 (check-worthiness in the US presidential debates 2016) for finding check-worthy claims in context.
Answer: It is called CW-USPD-2016 (check-worthiness in the US presidential debates 2016) for finding check-worthy claims in context.
Question: How do you? How do you plant flowers
Answer: To begin planting flowers, you will first dig a hole enough to fit a seed. Next you will cover it with dirt to fill the hole. finally pour some water over your covered up seed and over the next few days make sure that it gets tons of sunlight and water and watch your plant grow.
Question: How many boilers did Juvenal have?
Evidence: Cantiere Navale Triestino built Juvenal in Monfalcone, near Trieste, Italy, launching her on 3 June 1928 and completing her in August. She was 556.0 ft (169.5 m) long, had a beam of 74.1 ft (22.6 m) and a draught of 29 ft 2 in (8.89 m). As built her tonnages were 13,247 GRT and 7,934 NRT.

Juvenal was only slightly smaller than the tanker C.O. Stillman, which was then the largest in the World and had been completed in Bremen that February.

Juvenal had 15 corrugated furnaces that heated five boilers with a combined heating surface of 17,735 square feet (1,648 m2). They supplied steam at 200 lbf/in2 to a pair of triple expansion engines built by the North East Marine Engineering Co Ltd of Sunderland, England. Between them the engines developed a total of 1,167 NHP and propelled her by twin screws.
Answer: five
Question: Which is better, a stock option or Restricted Stock Unit (RSU)?
Answer: It is not possible to say that either one is better than the other. A stock option gives someone the right to buy a stock at a certain price (the “strike price”) at some point in the future. An RSU is a grant of a stock; the recipient does not pay money for it. An advantage of stock options compared to RSUs is that the gain between the strike price and the selling price is generally treated as a long-term capital gain, whereas the grant price of an RSU is treated as income, which is generally taxed at a higher rate. On the other hand, an advantage of RSUs is that they always have a nonzero value, whereas a stock option can become worthless if the stock price declines below the strike price.
Question: Which of the following numbers are odd and which are even: 1, 35, 72, 64, 103, 29, 16, 41, 22
Answer: These numbers are odd: 1, 35, 103, 29, 41. And these numbers are even: 72, 64, 16, 22.
Question: What makes a Squishmallow resellable?
Evidence: Due to the demand for the toy, Squishmallows are often sold by resellers for an increased price. The average resell price for a Squishmallow depends on the size, condition, and rarity of the specific item. Some limited edition or high-demand Squishmallows are sold by resellers and collectors for hundreds or thousands of dollars. Jack the Black Cat, known for its closed white eyes and white whiskers, is one of the rarest Squishmallows sold to date. KellyToys introduced the limited edition stuffed animal on their website in 2020, where it sold out within two hours. Third party websites like eBay host listings for Jack the Black Cat valued at nearly $2,000. Among the many Squishmallows that are sold, some of the most popular include Connor the Cow, Malcolm the Mushroom, Archie the Axolotl, and Philippe the Frog. There are reports that resellers are harassed and doxxed by the community.
Answer: Squishmallows are a highly demanded toy and also often are sold as limited edition items. As a result, Squishmallows that are more unique and rare can often be sold or higher value later. One example is Jack the Black Cat which has been listed on eBay for nearly $2,000.
Question: Given the following paragraph about the observation deck of the Burj Khalifa, what's offered on the 124th floor observation deck?
Evidence: An outdoor observation deck, named At the Top, opened on 5 January 2010 on the 124th floor. At 452 m (1,483 ft), it was the highest outdoor observation deck in the world when it opened. Although it was surpassed in December 2011 by Cloud Top 488 on the Canton Tower, Guangzhou at 488 m (1,601 ft), Burj Khalifa opened the 148th floor SKY level at 555 m (1,821 ft), once again giving it the highest observation deck in the world on 15 October 2014, until the Shanghai Tower opened in June 2016 with an observation deck at a height of 561 metres. The 124th floor observation deck also features the electronic telescope, an augmented reality device developed by Gsmprjct° of Montréal, which allows visitors to view the surrounding landscape in real-time, and to view previously saved images such as those taken at different times of day or under different weather conditions. To reduce the daily rush of sightseers, management allows visitors to purchase tickets in advance for a specific date and time, at a 75% discount on tickets purchased on the spot.
Answer: The 124th floor observation deck of the Burj Khalifa offers an augmented reality device called the electronic telescope which allows visitors to view surrounding landscapes in real-time as well as saved images.
Question: How did they detect entity mentions?
Evidence: In an offline step, we organize the content of each training instance in a graph connecting mentions of candidate answers within and across supporting documents. For a given query $q = \langle s, r, ? \rangle $ , we identify mentions in $S_q$ of the entities in $C_q \cup \lbrace s\rbrace $ and create one node per mention. This process is based on the following heuristic:
we consider mentions spans in $S_q$ exactly matching an element of $C_q \cup \lbrace s\rbrace $ . Admittedly, this is a rather simple strategy which may suffer from low recall.
we use predictions from a coreference resolution system to add mentions of elements in $C_q \cup \lbrace s\rbrace $ beyond exact matching (including both noun phrases and anaphoric pronouns). In particular, we use the end-to-end coreference resolution by BIBREF16 .
we discard mentions which are ambiguously resolved to multiple coreference chains; this may sacrifice recall, but avoids propagating ambiguity.
 For a given query $q = \langle s, r, ? \rangle $ , we identify mentions in $S_q$ of the entities in $C_q \cup \lbrace s\rbrace $ and create one node per mention. This process is based on the following heuristic:

we consider mentions spans in $S_q$ exactly matching an element of $C_q \cup \lbrace s\rbrace $ . Admittedly, this is a rather simple strategy which may suffer from low recall.

we use predictions from a coreference resolution system to add mentions of elements in $C_q \cup \lbrace s\rbrace $ beyond exact matching (including both noun phrases and anaphoric pronouns). In particular, we use the end-to-end coreference resolution by BIBREF16 .

we discard mentions which are ambiguously resolved to multiple coreference chains; this may sacrifice recall, but avoids propagating ambiguity.
Answer: Exact matches to the entity string and predictions from a coreference resolution system
Question: When was the HMS St David launched
Evidence: HMS St David was a 54-gun fourth rate ship of the line of the English Royal Navy, launched in 1667 at Lydney.

She foundered in Portsmouth Harbour in 1689  and was raised in 1691 under the supervision of Edmund Dummer, Surveyor of the Navy.

The ship was later hulked and finally sold in 1713.
Answer: The HMS St David was a 54-gun fourth rate ship of the line of the English Royal Navy, launched in 1667 at Lydney.

She foundered in Portsmouth Harbour in 1689 and was raised in 1691 under the supervision of Edmund Dummer, Surveyor of the Navy.

The ship was later hulked and finally sold in 1713.
Question: Alfred Jingle appears in which Dickens novel
Answer: The Pickwick Papers
Question: Summarise the following text using different wording than in the original: "A well-known Russian military blogger was killed in an explosion at a cafe in St. Petersburg on Sunday, officials said, in what appeared to be an audacious attack on a high-profile pro-Kremlin figure. Vladlen Tatarsky died when a blast tore through the cafe where he was appearing as a guest of a pro-war group called Cyber Front Z. Authorities said they were treating the case as suspected murder. Twenty-five other people were injured in the blast, 19 of whom were hospitalized, the city’s governor said. The Russian Ministry of Health said six people were in critical condition. Investigators were questioning everyone who was inside the cafe, state media reported. Photos of the scene showed extensive damage to the building in which the cafe was located."
Answer: Vladlen Tatarsky was a prominent military blogger from Russia. He died last Sunday as a result of an explosion that took place in a cafe in St. Petersburg injuring 25 people. The Russian authorities suspect this to be a murder and are investigating further.
Question: Give me a sample of three of Australian Animals.
Answer: Kangaroo, Koala and Emu are three well known Australian Animals.
Question: What are some modern examples of companies that have harnessed the power of network effects?
Evidence: In economics, a network effect (also called network externality or demand-side economies of scale) is the phenomenon by which the value or utility a user derives from a good or service depends on the number of users of compatible products. Network effects are typically positive, resulting in a given user deriving more value from a product as more users join the same network. The adoption of a product by an additional user can be broken into two effects: an increase in the value to all other users ( "total effect") and also the enhancement of other non-users' motivation for using the product ("marginal effect").

Network effects can be direct or indirect. Direct network effects arise when a given user's utility increases with the number of other users of the same product or technology, meaning that adoption of a product by different users is complementary. This effect is separate from effects related to price, such as a benefit to existing users resulting from price decreases as more users join. Direct network effects can be seen with social networking services, including Twitter, Facebook, Airbnb, Uber, and LinkedIn; telecommunications devices like the telephone; and instant messaging services such as MSN, AIM or QQ. Indirect (or cross-group) network effects arise when there are "at least two different customer groups that are interdependent, and the utility of at least one group grows as the other group(s) grow". For example, hardware may become more valuable to consumers with the growth of compatible software.

Network effects are commonly mistaken for economies of scale, which describe decreasing average production costs in relation to the total volume of units produced. Economies of scale are a common phenomenon in traditional industries such as manufacturing, whereas network effects are most prevalent in new economy industries, particularly information and communication technologies. Network effects are the demand side counterpart of economies of scale, as they function by increasing a customer's willingness to pay due rather than decreasing the supplier's average cost.

Upon reaching critical mass, a bandwagon effect can result. As the network continues to become more valuable with each new adopter, more people are incentivized to adopt, resulting in a positive feedback loop. Multiple equilibria and a market monopoly are two key potential outcomes in markets that exhibit network effects. Consumer expectations are key in determining which outcomes will result.
Answer: Examples of modern companies that have harnessed the power of network effects include social networking services such as: TikTok, Youtube, Twitter, Instagram, Facebook, Airbnb, Uber, and LinkedIn.