DataHammer/scimrc huggingface dataset:
Question: Which MLB baseball team has the most World Series wins?
Answer: The World Series is the annual championship series of Major League Baseball (MLB) and concludes the MLB postseason. First played in 1903, the World Series championship is a best-of-seven playoff and is a contest between the champions of baseball's National League (NL) and American League (AL). Often referred to as the "Fall Classic", the modern World Series has been played every year since 1903 with two exceptions: in 1904, when the NL champion New York Giants declined to play the AL champion Boston Americans; and in 1994, when the series was canceled due to the players' strike.

The best-of-seven style has been the format of all World Series except in 1903, 1919, 1920, and 1921, when the winner was determined through a best-of-nine playoff. Although the large majority of contests have been played entirely during the month of October, a small number of Series have also had games played during September and November. The Series-winning team is awarded the Commissioner's Trophy. Players, coaches and others associated with the team are generally given World Series rings to commemorate their victory; however, they have received other items such as pocket watches and medallions in the past. The winning team is traditionally invited to the White House to meet the President of the United States.

A total of 118 World Series have been contested through 2022, with the AL champion winning 67 and the NL champion winning 51. The New York Yankees of the AL have played in 40 World Series, winning 27 – the most championship appearances and most victories by any team amongst the major North American professional sports leagues. The Dodgers of the NL have the most losses with 14, while the Yankees have the most losses among AL teams with 13. The St. Louis Cardinals have won 11 championships, the most championships among NL clubs and second-most all-time behind the Yankees, and have made 19 total appearances, third-most among NL clubs. The Dodgers have represented the NL the most in the World Series with 21 appearances.

The Seattle Mariners are the only current MLB franchise that has never appeared in a World Series; the San Diego Padres, Colorado Rockies, Texas Rangers, Tampa Bay Rays, and Milwaukee Brewers have all played in the Series but have never won it. The Los Angeles Angels, Arizona Diamondbacks and Washington Nationals are the only teams who have won their only World Series appearance, and the Toronto Blue Jays and the Miami Marlins have won both of their World Series appearances. The Toronto Blue Jays are the only franchise from outside the United States to appear in and win a World Series, winning in 1992 and 1993. The Houston Astros are the only franchise to have represented both the NL (2005) and the AL (2017, 2019, 2021, 2022), winning the Series in 2017 and 2022.

The current (2022) World Series champions are the Houston Astros.
Question: What is the etymology of the word cookie?
Evidence: The word cookie dates from at least 1701 in Scottish usage where the word meant "plain bun", rather than thin baked good, and so it is not certain whether it is the same word. From 1808, the word "cookie" is attested "...in the sense of "small, flat, sweet cake" in American English. The American use is derived from Dutch koekje "little cake," which is a diminutive of "koek" ("cake"), which came from the Middle Dutch word "koke". Another claim is that the American name derives from the Dutch word koekje or more precisely its informal, dialect variant koekie which means little cake, and arrived in American English with the Dutch settlement of New Netherland, in the early 1600s.
Answer: The earliest known usage of the work cookie comes from 1701 in Scotland, where it meant "plain bun".  Starting in 1808 the term was associated with small, flat, sweet cakes as part of American English, which is believed to be derived from the Dutch word keokie.
Question: How was Elon Musk involved in Paypal?
Evidence: Individuals whom the media refers to as members of the PayPal Mafia include:

Peter Thiel, PayPal founder and former chief executive officer who is sometimes referred to as the "don" of the PayPal Mafia
Max Levchin, founder and chief technology officer at PayPal
Elon Musk, co-founder of Zip2, founder of X.com which merged with Confinity to form PayPal. Musk later founded SpaceX, co-founded Tesla, Inc., co-founded OpenAI, Neuralink, founded The Boring Company, and became owner of Twitter, Inc.
David O. Sacks, former PayPal COO who later founded Geni.com and Yammer
Scott Banister, early advisor and board member at PayPal.
Roelof Botha, former PayPal CFO who later became a partner and Senior Steward of venture capital firm Sequoia Capital
Steve Chen, former PayPal engineer who co-founded YouTube.
Reid Hoffman, former executive vice president who later founded LinkedIn and was an early investor in Facebook, Aviary
Ken Howery, former PayPal CFO who became a partner at Founders Fund
Chad Hurley, former PayPal web designer who co-founded YouTube
Eric M. Jackson, who wrote the book The PayPal Wars and became chief executive officer of WND Books and co-founded CapLinked
Jawed Karim, former PayPal engineer who co-founded YouTube
Jared Kopf, former PayPal (executive assistant to Peter Thiel) who co-founded Slide, HomeRun and NextRoll
Dave McClure, former PayPal marketing director, a super angel investor for start up companies
Andrew McCormack, co-founder of Valar Ventures
Luke Nosek, PayPal co-founder and former vice president of marketing and strategy, became a partner at Founders Fund with Peter Thiel and Ken Howery
Keith Rabois, former executive at PayPal who later worked at LinkedIn, Slide, Square, Khosla Ventures, and currently with Peter Thiel at Founders Fund, and personally invested in Tokbox, Xoom, Slide, LinkedIn, Geni, Room 9 Entertainment, YouTube, and Yelp
Jack Selby, former vice president of corporate and international development at PayPal who co-founded Clarium Capital with Peter Thiel, later becoming managing director of Grandmaster Capital Management
Premal Shah, former product manager at PayPal, became the founding president of Kiva.org
Russel Simmons, former PayPal engineer who co-founded Yelp Inc.
Jeremy Stoppelman, former vice president of technology at PayPal who later co-founded Yelp
Yishan Wong, former engineering manager at PayPal, later worked at Facebook and became the CEO of Reddit
Answer: Elon Musk founded X.com, which merged with Confinity to form Paypal.
Question: Give me different ways I can travel from one place to another
Answer: mode of transport can involve car, bus, cycle, airplane along with walk, run, swim, crawl and many more.
Question: What are popular young adult books?
Answer: Young adult novels typically tell a coming to age story with a main character in their teens or early adulthood.  From 2000-2015, common books for young adults are Harry Potter, Divergent, and The Hunger Games. Since them, young adult novels are more often showing themes of diversity, inclusion, and overcoming adversity and less focused on action-based storytelling. A popular graphic novel series, Heartstopper, is a good example of a popular book focused on DEI. This eventually turned into a high-profile television show on Netflix.
Question: What is Type 2 Diabetes?
Evidence: Type 2 diabetes, formerly known as adult-onset diabetes, is a form of diabetes mellitus that is characterized by high blood sugar, insulin resistance, and relative lack of insulin.
Answer: Type 2 diabetes, formerly known as adult-onset diabetes, is a form of diabetes mellitus that is characterized by high blood sugar, insulin resistance, and relative lack of insulin. Common symptoms include increased thirst, frequent urination, and unexplained weight loss.  Symptoms may also include increased hunger, feeling tired, and sores (wounds) that do not heal.  Often symptoms come on slowly. Long-term complications from high blood sugar include heart disease, strokes, diabetic retinopathy which can result in blindness, kidney failure, and poor blood flow in the limbs which may lead to amputations. The sudden onset of hyperosmolar hyperglycemic state may occur; however, ketoacidosis is uncommon.
Question: Choose the word which is different from the rest:  Trunk, Tree, Fruit, Leaf, Flower
Answer: All others are parts of a tree.
Question: What technique do they propose?
Evidence: Neural Networks have proven to be useful for automating tasks such as question answering, system response, and language generation considering large textual datasets. In learning systems, bias can be defined as the negative consequences derived by the implicit association of patterns that occur in a high-dimensional space. In dialogue systems, these patterns represent associations between word embeddings that can be measured by a Cosine distance to observe male- and female-related analogies that resemble the gender stereotypes of the real world. We propose an automatic technique to mitigate bias in language generation models based on the use of an external memory in which word embeddings are associated to gender information, and they can be sparsely updated based on content-based lookup.
The main contributions of our work are the following:
We introduce a novel architecture that considers the notion of a Fair Region to update a subset of the trainable parameters of a Memory Network.
We experimentally show that this architecture leads to mitigate gender bias amplification in the automatic generation of text when extending the Sequence2Sequence model.
We propose an automatic technique to mitigate bias in language generation models based on the use of an external memory in which word embeddings are associated to gender information, and they can be sparsely updated based on content-based lookup.
Answer: An automatic technique to mitigate bias in language generation models based on the use of an external memory in which word embeddings are associated to gender information.
Question: Can the model proposed by the author solve the problem effectively through experiments?
Evidence: In this work, we introduce a meta neural network, which can generate a compositional network to dynamically compose constituents over tree structure. The parameters of compositional function vary from position to position and from sample to sample, allowing for more sophisticated operations on the input.
To evaluate our models, we choose two typical NLP tasks involving six datasets. The qualitative and quantitative experiment results demonstrate the effectiveness of our models.
To evaluate our models, we choose two typical NLP tasks involving six datasets. The qualitative and quantitative experiment results demonstrate the effectiveness of our models
Answer: Yes.
Question: Which models do they use as baselines on the Atomic dataset?
Evidence: We compared our proposed model with the following four baseline methods:
RNN-based Seq2Seq proposed by BIBREF4 (BIBREF4) for the If-Then reasoning on Atomic.
Variational Seq2Seq combines a latent variable with the encoder-decoder structure through converting the last hidden state of RNN encoder into a Gaussian distributed latent variable BIBREF8.
VRNMT Propose by BIBREF19 (BIBREF19), VRNMT combines CVAE with attention-based encoder-decoder framework through introduces a latent variable to model the semantic distribution of targets.
CWVAE-Unpretrained refers to the CWVAE model without the pretrain stage.
Note that, for each baseline method, we train distinct models for each distinct inference dimension, respectively.
FLOAT SELECTED: Table 6: Average perplexity and BLEU scores (reported in percentages) for the top 10 generations under each inference dimension of Atomic. The the best result for each dimension is emboldened.
We compared our proposed model with the following four baseline methods:

RNN-based Seq2Seq proposed by BIBREF4 (BIBREF4) for the If-Then reasoning on Atomic.

Variational Seq2Seq combines a latent variable with the encoder-decoder structure through converting the last hidden state of RNN encoder into a Gaussian distributed latent variable BIBREF8.

VRNMT Propose by BIBREF19 (BIBREF19), VRNMT combines CVAE with attention-based encoder-decoder framework through introduces a latent variable to model the semantic distribution of targets.

CWVAE-Unpretrained refers to the CWVAE model without the pretrain stage.

Note that, for each baseline method, we train distinct models for each distinct inference dimension, respectively.
FLOAT SELECTED: Table 6: Average perplexity and BLEU scores (reported in percentages) for the top 10 generations under each inference dimension of Atomic. The the best result for each dimension is emboldened.
Answer: The answers are shown as follows:
* RNN-based Seq2Seq
* Variational Seq2Seq
* VRNMT 
* CWVAE-Unpretrained
Question: From the text, how long after the events of Return of the Jedi is the Mandalorian series set?  Convert years into months, and use letters to spell out the answer.
Evidence: The Mandalorian is an American space Western television series created by Jon Favreau for the streaming service Disney+. It is the first live-action series in the Star Wars franchise, beginning five years after the events of Return of the Jedi (1983), and stars Pedro Pascal as the title character, a lone bounty hunter who goes on the run to protect the Force-sensitive child Grogu. Starting in the third season, Katee Sackhoff also stars as Mandalorian Bo-Katan Kryze, following her appearance in the second season.
Answer: sixty
Question: Are alpacas and llamas the same thing?
Answer: No, alpacas and llamas are related species but are not the same species. Both are natives of South America, but are slightly different sizes and have different physical features
Question: Which is a species of fish? Lung or Lungfish
Answer: Lungfish
Question: Identify which instrument is string or percussion: Fiddlesticks, Tricordia
Answer: Tricordia is string, Fiddlesticks is percussion.
Question: Who wrote Howl's Moving Castle?
Evidence: Howl's Moving Castle is a fantasy novel by British author Diana Wynne Jones, first published in 1986 by Greenwillow Books of New York. It was a runner-up for the annual Boston Globe–Horn Book Award, and won the Phoenix Award twenty years later. It was adapted into a critically acclaimed 2004 animated film of the same name, which was nominated for the Academy Award for Best Animated Feature.
Answer: Howl's Moving Castle is a fantasy novel by British author Diana Wynne Jones.
Question: What external sources of information are used?
Evidence: In this report we have presented a sentiment analysis tool for Twitter posts. We have discussed the characteristics of Twitter that make existing sentiment analyzers perform poorly. The model proposed in this report has addressed the challenges by using normalization methods and features specific to this media. We show that using external knowledge outside the tweet text (from landing pages of URLs) and user features can significantly improve performance. We have presented experimental results and comparison with state-of-the-art tools.
 We show that using external knowledge outside the tweet text (from landing pages of URLs) and user features can significantly improve performance. 
Answer: The answers are shown as follows:
* landing pages of URLs
Question: What is the biggest dog breed in the world?
Answer: The great dane, originated from Germany. It is one of the two largest dog breeds together with the Irish Wolfhound.
Question: What does the paper investigate?
Evidence: Predicting stock market movements is a well-known problem of interest. Now-a-days social media is perfectly representing the public sentiment and opinion about current events. Especially, twitter has attracted a lot of attention from researchers for studying the public sentiments. Stock market prediction on the basis of public sentiments expressed on twitter has been an intriguing field of research. Previous studies have concluded that the aggregate public mood collected from twitter may well be correlated with Dow Jones Industrial Average Index (DJIA). The thesis of this work is to observe how well the changes in stock prices of a company, the rises and falls, are correlated with the public opinions being expressed in tweets about that company. Understanding author's opinion from a piece of text is the objective of sentiment analysis. The present paper have employed two different textual representations, Word2vec and N-gram, for analyzing the public sentiments in tweets. In this paper, we have applied sentiment analysis and supervised machine learning principles to the tweets extracted from twitter and analyze the correlation between stock market movements of a company and sentiments in tweets. In an elaborate way, positive news and tweets in social media about a company would definitely encourage people to invest in the stocks of that company and as a result the stock price of that company would increase. At the end of the paper, it is shown that a strong correlation exists between the rise and falls in stock prices with the public sentiments in tweets.
Previous studies have concluded that the aggregate public mood collected from twitter may well be correlated with Dow Jones Industrial Average Index (DJIA). The thesis of this work is to observe how well the changes in stock prices of a company, the rises and falls, are correlated with the public opinions being expressed in tweets about that company.
Answer: Investigate the correlation of sentiments extracted from Twitter with the Dow Jones Industrial Average (DJIA).
Question: What is orange wine?
Answer: Orange wine is a term given to white wines that have "skin contact" during the wine making process. Unlike true white wines, where contact between the pressed white grape juice and the white grape skins is minimised, for an orange wine the pressed juice will macerate with the skins, similar to the process for making a red wine. The depth of colour and the level of tannin present in the resulting wine will be determined, largely, by the length of this maceration. Due to the presence of tannin, orange wines can often taste "funky" compared to white wines, and are very popular with proponents of the natural wine movement.
Question: List all the awards received by  Devon Dikeou in chronological order
Evidence: Devon Dikeou (born 1963) is an American artist, publisher, and art collector. Dikeou’s practice investigates the "in-between" — subtle interactions between artist, art object, viewer, space, and context.
Life and education
Devon Dikeou is originally from Denver, Colorado. She received a B.A. from Brown University in 1986 and an M.F.A. from the School of Visual Arts in 1988.
Since the start of her career in the early 1990s, Dikeou has received several artist awards and nominations including The Sue Canon Award from the Museum of Contemporary Art Denver (2007), Assistance League of Houston (2011 and 2013), Santo Foundation (2012), and the DAM Key Award from Denver Art Museum (2017).
Exhibitions


Devon Dikeou, "What's Love Got To Do With It: From Sculpture," 1991-ongoing
Dikeou has exhibited at numerous international museums, foundations, and galleries including the New Museum, The Contemporary Austin, Boulder Museum of Contemporary Art, Artpace San Antonio, Tricia Collins Grand Salon, James Fuentes Gallery in 2017 and 2018, 179 Canal, Kai Matsumiya, and Postmasters. She has also shown at art fairs, including Art Basel Statements, The Armory Show, Independent, NADA Miami Beach, and NADA New York.
Dikeou's mid-career retrospective "Mid-Career Smear" opened at The Dikeou Collection in February 2020.
zingmagazine


zingmagazine issue 23
Devon Dikeou published the first issue of zingmagazine in 1995. zingmagazine is composed of rotating multi-page curatorial projects organized by artists and arts professionals.
The Dikeou Collection


zingmagazine
In 1998, Devon Dikeou founded the Dikeou Collection along with her brother Pany Dikeou. The Dikeou Collection is a private contemporary art collection in downtown Denver, Colorado, and features work from over 40 international artists and functions as extension of zingmagazine.
Answer: The awards received by Devon Dikeou are as follows:
- The Sue Canon Award from the Museum of Contemporary Art Denver (2007)
- Assistance League of Houston (2011)
- Santo Foundation (2012)
- Assistance League of Houston (2013)
- DAM Key Award from Denver Art Museum (2017)
Question: Classify the following as either Australian flora or fauna: kangaroo, wattle, emu, possum, echidna, kookaburra, macadamia, eucalyptus.
Answer: Kangaroo, emu, possum and echidna are Australian fauna. Wattle, macadamia and eucalyptus are Australian flora.
Question: Which three Twitter sentiment classification datasets are used for experiments?
Evidence: Stanford - Twitter Sentiment Corpus (STS Corpus): STS Corpus contains 1,600K training tweets collected by a crawler from BIBREF0 . BIBREF0 constructed a test set manually with 177 negative and 182 positive tweets. The Stanford test set is small. However, it has been widely used in different evaluation tasks BIBREF0 BIBREF5 BIBREF13 .
Sanders - Twitter Sentiment Corpus: This dataset consists of hand-classified tweets collected by using search terms: INLINEFORM0 , #google, #microsoft and #twitter. We construct the dataset as BIBREF14 for binary classification.
Health Care Reform (HCR): This dataset was constructed by crawling tweets containing the hashtag #hcr BIBREF15 . Task is to predict positive/negative tweets BIBREF14 .
Stanford - Twitter Sentiment Corpus (STS Corpus): STS Corpus contains 1,600K training tweets collected by a crawler from BIBREF0 . BIBREF0 constructed a test set manually with 177 negative and 182 positive tweets. The Stanford test set is small. However, it has been widely used in different evaluation tasks BIBREF0 BIBREF5 BIBREF13 .

Sanders - Twitter Sentiment Corpus: This dataset consists of hand-classified tweets collected by using search terms: INLINEFORM0 , #google, #microsoft and #twitter. We construct the dataset as BIBREF14 for binary classification.

Health Care Reform (HCR): This dataset was constructed by crawling tweets containing the hashtag #hcr BIBREF15 . Task is to predict positive/negative tweets BIBREF14 .
Answer: The answers are shown as follows:
* Stanford - Twitter Sentiment Corpus (STS Corpus)
* Sanders - Twitter Sentiment Corpus
* Health Care Reform (HCR)
Question: What are lots of different smells you might experience when going into a candle store?
Answer: Beachwood, Ocean breeze, coconut lime, Jasmine, Musk and Apple Cider
Question: What two new phrase or sentence representation learning objectives do the authors propose?
Evidence: Unsupervised methods for learning distributed representations of words are ubiquitous in today's NLP research, but far less is known about the best ways to learn distributed phrase or sentence representations from unlabelled data. This paper is a systematic comparison of models that learn such representations. We find that the optimal approach depends critically on the intended application. Deeper, more complex models are preferable for representations to be used in supervised systems, but shallow log-linear models work best for building representation spaces that can be decoded with simple spatial distance metrics. We also propose two new unsupervised representation-learning objectives designed to optimise the trade-off between training time, domain portability and performance.
We also propose two new phrase or sentence representation learning objectives - Sequential Denoising Autoencoders (SDAEs) and FastSent, a sentence-level log-linear bag-of-words model.
Answer: Sequential Denoising Autoencoders (SDAEs) and FastSent, a sentence-level log-linear bag-of-words model.
Question: What football team did Jerome Bettis play for?
Answer: The Steelers