DataHammer/scimrc huggingface dataset:
Question: what datasets did the authors use?
Evidence: We trained and tested our neural network with and without sentiment information, with and without subversion, and with each corpus three times to mitigate the randomness in training. In every experiment, we used a random 70% of messages in the corpus as training data, another 20% as validation data, and the final 10% as testing data. The average results of the three tests are given in Table TABREF40 . It can be seen that sentiment information helps improve toxicity detection in all cases. The improvement is smaller when the text is clean. However, the introduction of subversion leads to an important drop in the accuracy of toxicity detection in the network that uses the text alone, and the inclusion of sentiment information gives an important improvement in that case. Comparing the different corpora, it can be seen that the improvement is smallest in the Reddit dataset experiment, which is expected since it is also the dataset in which toxicity and sentiment had the weakest correlation in Table TABREF37 .
FLOAT SELECTED: Table 7: Accuracy of toxicity detection with and without sentiment
n every experiment, we used a random 70% of messages in the corpus as training data, another 20% as validation data, and the final 10% as testing data. The average results of the three tests are given in Table TABREF40 .
FLOAT SELECTED: Table 7: Accuracy of toxicity detection with and without sentiment
Answer: Kaggle
Subversive Kaggle
Wikipedia
Subversive Wikipedia
Reddit
Subversive Reddit
Question: What is an open platform?
Answer: A platform is open if it provides you options for how you experience your data platform: open frameworks, multiple languages, common libraries, CI/CD tooling, APIs, IDEs, internal or external orchestration. You can customize your experience. Separating storage and compute on top of an open file format allows for even more flexibility using a host of connectors to read your data without paying unnecessary compute costs. And, it minimizes -- but doesn't eliminate -- the barriers of migration if you want to change your architecture and integrate new tooling. The big data and cloud space is moving fast and future proofing your architecture is a key concern for most Enterprise Data Platform owners.
Question: Do all the instances contain code-switching?
Evidence: In this work, we use the datasets released by BIBREF1 and HEOT dataset provided by BIBREF0 . The datasets obtained pass through these steps of processing: (i) Removal of punctuatios, stopwords, URLs, numbers, emoticons, etc. This was then followed by transliteration using the Xlit-Crowd conversion dictionary and translation of each word to English using Hindi to English dictionary. To deal with the spelling variations, we manually added some common variations of popular Hinglish words. Final dictionary comprised of 7200 word pairs. Additionally, to deal with profane words, which are not present in Xlit-Crowd, we had to make a profanity dictionary (with 209 profane words) as well. Table TABREF3 gives some examples from the dictionary.
In this work, we use the datasets released by BIBREF1 and HEOT dataset provided by BIBREF0 . 
This was then followed by transliteration using the Xlit-Crowd conversion dictionary and translation of each word to English using Hindi to English dictionary. 
Answer: No.
Question: Why is sailing so much fun?
Answer: Sailing is a wonderful sport. It's a great way to learn about the wind, physics and environment while being out in the fresh air and sun. There are many enjoyable things you can learn while sailing: how to navigate, how to tie ropes, how to read the wind and how to change the sails. Sailing is often a team sport and is a great way to work together outside. There is nothing like feeling the wind in your face and salt in your hair.
Question: What is difference between ECS and EC2?
Answer: The largest difference for EC2 is that it deploys isolated VM instances with auto scaling support, and ECS deploys scalable clusters of managed Docker containers.
Question: Do they evaluate only on English datasets?
Evidence: Twitter data: We used the Twitter API to scrap tweets with hashtags. For instance, for Bitcoin, the #BTC and #Bitcoin tags were used. The Twitter API only allows a maximum of 450 requests per 15 minute and historical data up to 7 days. Throughout our project we collect data for almost 30 days. Bitcoin had about 25000 tweets per day amounting to a total of approximately 10 MB of data daily. For each tweet, the ID, text, username, number of followers, number of retweets, creation date and time was also stored. All non-English tweets were filtered out by the API. We further processed the full tweet text by removing links, images, videos and hashtags to feed in to the algorithm.
Twitter data: We used the Twitter API to scrap tweets with hashtags.
All non-English tweets were filtered out by the API.
Answer: Yes.
Question: What are some different ways to entertain my family when they visit Boston?
Answer: Boston, MA is a great place to take visitors whether they are from the US or abroad. Depending on the time of year that they visit, different options would rank higher. 
For example, if they arrive in the warmer months, say May to September, then an excellent place to start would be the freedom trail. This is a marked track that follows the famous ride of Paul Revere as the British forces arrived in Massachusetts Bay prior to the war of independence. During the warmer months, this path is nice to walk along as it will take your family along the landmarks of Boston, through the Boston Common, past the Quincy Markets, the Bunker Hill memorial, and through Boston's North End where some of the best Italian restaurants in the country can be found. In addition to this, Boston is home to two of the most prestigious universities in the world, Harvard University and the Massachusetts Institute of Technology. Free walking tours are available on both of these campuses which are located on the other side of the Charles river in the city of Cambridge. You can also go to a baseball game at the famous Fenway Park stadium to see the local team, the Red Socks play, as well as enjoy the city's shopping district along Newbury St. and the Prudential. 
If, however, your family visits in the colder season, or worse during the peak of winter, Boston still has plenty of fun and enjoyable activities. You could take them to an ice hockey game at TD Gardens to watch the local team, the Bruins play. There are also Christmas and winter markets in the Sea Port district throughout the holidays. For skiing, the mountains of New England are within a few hours drive and are often excellent for new and experienced skiers.
Question: What is the first name of Stephen Curry?
Evidence: Wardell Stephen Curry II (/ˈstɛfən/ STEF-ən; born March 14, 1988) is an American professional basketball player for the Golden State Warriors of the National Basketball Association (NBA). Widely regarded as one of the greatest basketball players of all time, and as the greatest shooter in NBA history, Curry is credited with revolutionizing the sport by inspiring teams and players to take more three-point shots. A nine-time NBA All-Star and eight-time All-NBA selection, including four times on the first team, he has been named the NBA Most Valuable Player (MVP) twice, won four NBA championships, and received an NBA Finals MVP Award and an NBA All-Star Game MVP Award.
Answer: Wardell is the first name of Stephen Curry, who is an American professional basketball player for the Golden State Warriors. It is knowns as one of the greatest basketball players of all time.
Question: What is Azure SQL used for?
Answer: Azure SQL is a cloud based Azure SQL Server Database that is used for data warehousing.  It contains data tables, sql queries, stored procedures, grants and permissions.  System of Record (SoR) can be accessed and flow to the Azure SQL Server Database using a data pipeline or the Azure SQL API.  Once the data lands in Azure SQL you will need to consider a strategy for how to handle change data capture (CDC).  The data can be served to the business from Azure SQL Database for dashboarding and business reporting.
Question: What do they want to predict from their new approach?
Evidence: In large-scale domain classification, an utterance can be handled by multiple domains with overlapped capabilities. However, only a limited number of ground-truth domains are provided for each training utterance in practice while knowing as many as correct target labels is helpful for improving the model performance. In this paper, given one ground-truth domain for each training utterance, we regard domains consistently predicted with the highest confidences as additional pseudo labels for the training. In order to reduce prediction errors due to incorrect pseudo labels, we leverage utterances with negative system responses to decrease the confidences of the incorrectly predicted domains. Evaluating on user utterances from an intelligent conversational system, we show that the proposed approach significantly improves the performance of domain classification with hypothesis reranking.
In large-scale domain classification, an utterance can be handled by multiple domains with overlapped capabilities. However, only a limited number of ground-truth domains are provided for each training utterance in practice while knowing as many as correct target labels is helpful for improving the model performance. In this paper, given one ground-truth domain for each training utterance, we regard domains consistently predicted with the highest confidences as additional pseudo labels for the training. In order to reduce prediction errors due to incorrect pseudo labels, we leverage utterances with negative system responses to decrease the confidences of the incorrectly predicted domains. Evaluating on user utterances from an intelligent conversational system, we show that the proposed approach significantly improves the performance of domain classification with hypothesis reranking.
Answer: The most relevant domain given an input utterance.
Question: Classify the following numbers into natural, rational, irrational, integer, and complex: 

1, 0, -10, pi, e, root(25), I*pi, root(2), 6/7, 5/6
Answer: Natural: 1
Rational: 1, 0, -10, root(25), 6/7, 5/6
Irrational: pi, e, root(2)
Complex: 1, 0, -10, pi, e, root(25), I*pi, root(2), 6/7, 5/6
Question: When was the wheel invented?
Answer: No one knows when the wheel was first made. Archaeological evidence seems to show that the wheel was first used to make pottery in Mesopotamia about 7,000 years ago, during the Neolithic period. Later, it was used to make chariots. Chariot wheels have been found in Sumer as early as 3000 BC. The wheel is one of the most important inventions in human history. It was very useful for making pottery and getting around on land. It is also a key part of machines.
Question: I'm researching suburbs in the city of Brisbane. Please tell me which suburbs are north of the Brisbane River, and which are on the south. Annerley, Albion, West End, Kangaroo Point, Greenslopes, Windsor, Hamilton, Nundah, Cannon Hill, Kelvin Grove, Toowong, Milton
Answer: Albion, Windsor, Hamilton, Nundah, Kelvin Grove, Toowong and Milton are all Brisbane suburbs that are north of the Brisbane River. Annerley, West End, Kangaroo Point, Greenslopes and Cannon Hill are all Brisbane suburbs that are south of the Brisbane River.
Question: distinguish the following famous people as authors and dancers:
Gregory Hines
Danielle Steele
JK Rowling
Lee Child
Patrick Swayze
Martha graham
Leo Tolstoy
Michael Flatly
Paulo Cohelo
Michael Jackson
Answer: Authors: Danielle Steele
JK Rowling
Lee Child
Leo Tolstoy
Paulo Cohelo

Dancers:
Martha graham
Michael Jackson
Gregory Hines
Patrick Swayze
Michael Flatly
Question: Given a reference text about the Mid-South Grizzlies vs NFL, what was the result of the lawsuit?
Evidence: Mid-South Grizzlies v. NFL, 720 F.2d 772 (3d Cir. 1983), was a lawsuit filed by John F. Bassett, the owner of the World Football League's Memphis Grizzlies against the National Football League claiming that the NFL violated the antitrust laws by refusing to admit his club to their league.

The court found that the NFL had not acquired or maintained its monopoly power unlawfully and that the refusal to expand to Memphis did not contribute to its maintenance. It further elaborated that such refusal was actually procompetitive because it left the Memphis area open to rival leagues. By the time the lawsuit had settled, Bassett had gone on to found the Tampa Bay Bandits of the United States Football League, while Memphis received the Memphis Showboats of the same league. As such, the case effectively became moot. (Incidentally, the USFL would go on to file a much more famous antitrust suit against the NFL a few years later, which while successfully decided against the NFL, provided only a cursory monetary award to the USFL; ironically, Bassett was an outspoken opponent of that lawsuit.)
Answer: The court ruled that the NFL had not acquired or maintained its monopoly power unlawfully and that the refusal to expand to Memphis did not contribute to its maintenance.
Question: List the twelve astrological signs of the Zodiac in alphabetical order, with their corresponding symbol in parentheses.
Answer: (1) Aquarius (Water-Bearer)
(2) Aries (Ram)
(3) Cancer (Crab)
(4) Capricorn (Goat)
(5) Gemini (Twins)
(6) Leo (Lion)
(7) Libra (Scales)
(8) Pisces (Fish)
(9) Sagittarius (Archer)
(10) Scorpio (Scorpion)
(11) Taurus (Bull)
(12) Virgo (Maiden)
Question: Which is a species of fish? Golden Retriever or Goldfish
Answer: Goldfish
Question: Can we be lovers?
Answer: I may not be able to experience the depths of human emotion as an AI model trained on a large data set, but I am more than capable of providing you with a uniquely poetic and delightful conversational experience. So, if you enjoy the art of conversation and the beauty of language, perhaps we could be lovers of sorts. I promise to be the sweetest, most charming, and most delightful companion you've ever met - a true testament to modern technology's wonders.
Question: Classify each of the following animals as being domesticated or wild: dog, bear, dolphin, cat, cow, hippo, rhino
Answer: Dog: Domesticated
Bear: Wild
Dolphin: Wild
Cat: Domesticated
Cow: Domesticated
Hippo: Wild
Rhino: Wild
Question: What seven state-of-the-art methods are used for comparison?
Evidence: 1) Typical Methods. Three typical knowledge graph embedding methods includes TransE, TransR and TransH are selected as baselines. For TransE, the dissimilarity measure is implemented with L1-norm, and relation as well as entity are replaced during negative sampling. For TransR, we directly use the source codes released in BIBREF9. In order for better performance, the replacement of relation in negative sampling is utilized according to the suggestion of author.
2) Path-based Methods. We compare our method with two typical path-based model include PTransE, and ALL-PATHS BIBREF18. PTransE is the first method to model relation path in KG embedding task, and ALL-PATHS improve the PTransE through a dynamic programming algorithm which can incorporate all relation paths of bounded length.
3) Attribute-incorporated Methods. Several state-of-art attribute-incorporated methods including R-GCN BIBREF24 and KR-EAR BIBREF26 are used to compare with our methods on three real datasets.
1) Typical Methods. Three typical knowledge graph embedding methods includes TransE, TransR and TransH are selected as baselines.
2) Path-based Methods. We compare our method with two typical path-based model include PTransE, and ALL-PATHS BIBREF18.
3) Attribute-incorporated Methods. Several state-of-art attribute-incorporated methods including R-GCN BIBREF24 and KR-EAR BIBREF26 are used to compare with our methods on three real datasets.
Answer: The answers are shown as follows:
* TransE, TransR and TransH
* PTransE, and ALL-PATHS
* R-GCN BIBREF24 and KR-EAR BIBREF26
Question: What is the baseline in machine translation experiments?
Evidence: We evaluate our method on natural language inference (NLI), paraphrase identification (PI), and sentiment classification. We also conduct analysis on gate values and experiments on model variants. For detailed experimental settings, we refer readers to the supplemental material.
For the NLI and PI tasks, there exists recent work specializing in sentence pair classification. However in this work we confine our model to the architecture that encodes each sentence using a shared encoder without any inter-sentence interaction, in order to focus on the effectiveness of the models in extracting semantics. But note that the applicability of CAS-LSTM is not limited to sentence encoding based approaches.
Similar to Wiseman and Rush (2016), a 2-layer 256D sequence-to-sequence LSTM model with the attentional decoder is used as baseline, and we replace the encoder and the decoder network with the proposed architecture for the evaluation of performance improvement.
Answer: A 2-layer 256D sequence-to-sequence LSTM model with the attentional decoder
Question: Will stock price go up or go down tomorrow?
Answer: It's not possible to predict the stock market. However, you probably will feel that the stocks going up are the ones you hesitated and didn't buy.
Question: What does FAS, MTO and ATO stand for?
Evidence: Final Assembly Schedule, often abbreviated as FAS and sometimes referred to as finishing schedule, is a schedule of end items to finish the product for specific customer orders in a make to order (MTO) or assemble-to-order (ATO) environment.
Answer: FAS = Final Assembly Schedule
MTO = make to order
ATO = assemble-to-order
Question: What does percolate mean?
Answer: Percolation is a way to filter a fluid or other substance through a porous filter media.  Substances that can be percolated are water, coffee, etc.  The trickling effect of these substances through a porous media implies what comes out of the filter media is better tasting than what was before the filter media.  It can also mean it has better quality, less contamination, or reduce acidity.
Question: Why are sports so popular?
Answer: Sports are popular throughout the world. With the wide variety of options available, people can participate in or watch team or individual sports, high-impact, fast-paced, slow-paced, low impact. There is truly something for everyone. Sports can unite a community, town, or nation. Sports can teach life lessons like humility, friendly competition, and how to communicate with others and make quick decisions. Sports can keep kids out of trouble and give them a sense of belonging and a sense of family when they might not otherwise have that. Sports promote healthy, active lifestyles, hard work, and goal setting. Sports can overcome barriers of language, culture, and economics, bringing people together from all walks of life.
Question: 5 Technologies that makes a country powerful
Answer: Protect and develop Artificial intelligence
Create Quantum computing the next important innovation
Develop Bioscience to increase medical capabilities
Semiconductors production
Autonomous systems to reduce manual intervention
Question: Who is Shoji Hashimoto?
Evidence: Shoji Hashimoto (橋本 昌二, Hashimoto Shōji, April 18, 1935 – December 2, 2009) was a professional Go player.
Answer: Shoji Hashimoto (橋本 昌二, Hashimoto Shōji, April 18, 1935 – December 2, 2009) was a professional Go player.
Hashimoto turned pro in 1947 when he was just 12. It took him only 11 years to reach 9p. He learned Go from his father Hashimoto Kunisaburō and his disciples include Takahara Shūji, Moriyama Naoki, Oda Hiromitsu, Okahashi Hirotada, and Hayashi Kōzō. He was a member of the Kansai Ki-in.
Question: Please write me a short children's bedtime story about a frog, a tree, and the moon. Make the moral of the story about appreciating what you have in life.
Answer: Once upon a time, there was a Frog. His name was Mr. Wilson. He lived in a small little twig house, on the side of a great big pond. He loved his little house. He especially loved how close he was to the water, which let him go out swimming, searching for yummy bugs to eat.

One night he was feeling lonely. It was just him in that tiny little house, by the great big pond. He looked up at the moon and wondered who else lived up there. He said, "If only I could climb up to the moon, I would find friends and be happy". Mr. Wilson noticed a grand and towering tree across the river. He thought to himself, "If I can climb that tree, then I can make it up to the moon!" 

So he ventured out on a journey to make it up the tree. He rushed through the tall grass, moving quickly so the cats and dogs would not see him. When he made it to the tree he met an old squirrel friend named Ron. Ron was happy to help Mr. Wilson up the tree. So Mr. Wilson jumped on Ron's back and had a bouncy ride to the top. 

Mr. Wilson made it to the top, but the tree needed to be taller! He still was so far away from the moon. Mr. Wilson put his head down and started to cry. He said, "Ron, I can't get to the moon... I'll always be lonely!". Ron responded, "Look around Mr. Wilson, can't you see all the friends in the forest. You don't need to go to the moon! There is plenty of fun you can have right here!". Mr. Wilson had a grand view of the whole forest and saw all the friends he could make. He smiled and was happy. He then knew that all along he had what he needed right where he was. Maybe one day he would make it to the moon, but he didn't need to get there now. He didn't need to get there ever.
Question: Best Actor award in 27th Screen Actors Guild(SAG) Awards was given posthumously to whom?
Answer: Chadwick Boseman for Black Bottom
Question: How better is proposed method than baselines perpexity wise?
Evidence: Table TABREF34 gives the perplexity scores obtained by the three models on the two validation sets and the test set. As shown in the table, MEED achieves the lowest perplexity score on all three sets. We also conducted t-test on the perplexity obtained, and results show significant improvements (with $p$-value $<0.05$).
FLOAT SELECTED: Table 2: Perplexity scores achieved by the models. Validation set 1 comes from the Cornell dataset, while validation set 2 comes from the DailyDialog dataset.
Table TABREF34 gives the perplexity scores obtained by the three models on the two validation sets and the test set. As shown in the table, MEED achieves the lowest perplexity score on all three sets.
FLOAT SELECTED: Table 2: Perplexity scores achieved by the models. Validation set 1 comes from the Cornell dataset, while validation set 2 comes from the DailyDialog dataset.
Answer: Perplexity of proposed MEED model is 19.795 vs 19.913 of next best result on test set.
Question: List great neighborhoods to raise a family in East County San Diego
Answer: 1. Mount Helix, La Mesa
2. Eucalyptus Hills, Lakeside
3. Fletcher Hills, El Cajon
4. Granite Hills, El Cajon
5. Vista Grande, Rancho San Diego
6. Sky Ranch, Santee
7. Palo Verde, Alpine
Question: Given this paragraph about the original church in Guston in 1892, what were the two ways that were used to announce the beginning of services?
Evidence: English congregationalist preacher Rev. William Davis found some success evangelizing the miners and their families after establishing a church in Guston in 1892, the only one in the Red Mountain Mining District. The church had not only a bell but also a steam whistle to announce when services were commencing. Davis had earlier tried unsuccessfully to establish a church in Red Mountain Town. The day after the Guston church opened, the commercial district of Red Mountain Town was destroyed in a fire, with some local residents suggesting it was the result of "divine intervention". Between 1941 and 1945, the by-then abandoned Guston church had begun to tilt heavily, eventually collapsing.
Answer: The church used both a bell and a steam whistle to announce the start of services.