DataHammer/scimrc huggingface dataset:
Question: What is Protestantism and when did it start?
Evidence: Protestantism is a branch of Christianity that follows the theological tenets of the Protestant Reformation, a movement that began seeking to reform the Catholic Church from within in the 16th century against errors, abuses, and discrepancies.

Protestantism emphasizes the Christian believer's justification by God in faith alone (sola fide) rather than by a combination of faith with good works as in Catholicism; the teaching that salvation comes by divine grace or "unmerited favor" only (sola gratia); the priesthood of all believers in the Church; and the sola scriptura ("scripture alone") that posits the Bible as the sole infallible source of authority for Christian faith and practice. Protestants reject the Catholic doctrine of papal supremacy, and have variant views on the number of sacraments, the real presence of Christ in the Eucharist, and matters of ecclesiastical polity and apostolic succession. Other Protestant denominations and non-denominational Protestants may be typically unconcerned about most of these theological issues and focus only on their perception of explicit Christian teachings in the Bible itself. The five solae of Lutheran and Reformed Christianity summarize basic theological differences in opposition to the Catholic Church. Today, it is the second-largest form of Christianity, with a total of 800 million to 1 billion adherents worldwide or about 37% of all Christians.
Answer: Ali Malekshahi
Question: What is baseball?
Answer: Baseball is a game played by millions of people and is a very popular sport.  Each team takes turns playing offense and defense.  The objective of the team hitting is to score runs by reaching base safely.  The objective the defense is to get the hitters out.  The team with the most runs at the end of the game wins.
Question: What is the difference between a trumpet and a trombone?
Answer: A trumpet is a smaller horn than a trombone, which leads the trumpet to have a higher pitch. The trumpet also has keys pressed by the fingers in various combinations to play different notes, while the trombone uses a slide.
Question: What was the Cold War?
Answer: The Cold War was a time period where the US and USSR were in high tensions with each other. Both had created nuclear weapons and they had lost their alliance from World War 2. The war technically never ended since the USSR was disbanded in 1991.
Question: Give me a list of the top US mobile service providers
Answer: The top US mobile service providers are:
Verizon
T-Mobile
Sprint
AT&T
Google
Mint
Cricket
Question: Name some characters of One Piece Straw Hat Pirates.
Answer: Monkey D. Luffy, Roronoa Zoro, Nami, Usopp, Sanji, Tony Tony Chopper, Nico Robin, Franky, Brook, Jimbei
Question: Which data set is used in the sentiment feature extraction model?
Evidence: As discussed above, sentiment clues play an important role for sarcastic sentence detection. In our work, we train a CNN (see Section SECREF5 for details) on a sentiment benchmark dataset. This pre-trained model is then used to extract features from the sarcastic datasets. In particular, we use Semeval 2014 BIBREF34 Twitter Sentiment Analysis Dataset for the training. This dataset contains 9,497 tweets out of which 5,895 are positive, 3,131 are negative and 471 are neutral. The fully-connected layer of the CNN used for sentiment feature extraction has 100 neurons, so 100 features are extracted from this pre-trained model. The final softmax determines whether a sentence is positive, negative or neutral. Thus, we have three neurons in the softmax layer.
In particular, we use Semeval 2014 (Rosenthal et al., 2014) Twitter Sentiment Analysis Dataset for the training.
Answer: Semeval 2014 (Rosenthal et al., 2014) Twitter Sentiment Analysis Dataset.
Question: What was the estimated Gini coefficient of South Africa during 2008-2009?
Evidence: In economics, the Gini coefficient, also known as the Gini index or Gini ratio, is a measure of statistical dispersion intended to represent the income inequality or the wealth inequality or the consumption inequality within a nation or a social group. It was developed by statistician and sociologist Corrado Gini.
The Gini coefficient measures the inequality among values of a frequency distribution, such as levels of income. A Gini coefficient of 0 reflects perfect equality, where all income or wealth values are the same, while a Gini coefficient of 1 (or 100%) reflects maximal inequality among values. For example, if everyone has the same income, the Gini coefficient will be 0. In contrast, a Gini coefficient of 1 indicates that within a group of people, a single individual has all the income or consumption, while all others have none.
The Gini coefficient was proposed by Corrado Gini as a measure of inequality of income or wealth.  For OECD countries, in the late 20th century, considering the effect of taxes and transfer payments, the income Gini coefficient ranged between 0.24 and 0.49, with Slovenia being the lowest and Mexico the highest. African countries had the highest pre-tax Gini coefficients in 2008–2009, with South Africa having the world's highest, estimated to be 0.63 to 0.7, although this figure drops to 0.52 after social assistance is taken into account, and drops again to 0.47 after taxation. The global income Gini coefficient in 2005 has been estimated to be between 0.61 and 0.68 by various sources.
Answer: In 2008–2009, the Gini coefficient for South Africa was estimated estimated to be 0.63 to 0.7.
Question: What classifiers do the authors experiment with?
Evidence: With the massive increase in social interactions on online social networks, there has also been an increase of hateful activities that exploit such infrastructure. On Twitter, hateful tweets are those that contain abusive speech targeting individuals (cyber-bullying, a politician, a celebrity, a product) or particular groups (a country, LGBT, a religion, gender, an organization, etc.). Detecting such hateful speech is important for analyzing public sentiment of a group of users towards another group, and for discouraging associated wrongful activities. It is also useful to filter tweets before content recommendation, or learning AI chatterbots from tweets.
The manual way of filtering out hateful tweets is not scalable, motivating researchers to identify automated ways. In this work, we focus on the problem of classifying a tweet as racist, sexist or neither. The task is quite challenging due to the inherent complexity of the natural language constructs – different forms of hatred, different kinds of targets, different ways of representing the same meaning. Most of the earlier work revolves either around manual feature extraction BIBREF0 or use representation learning methods followed by a linear classifier BIBREF1 , BIBREF2 . However, recently deep learning methods have shown accuracy improvements across a large number of complex problems in speech, vision and text applications. To the best of our knowledge, we are the first to experiment with deep learning architectures for the hate speech detection task.
In this paper, we experiment with multiple classifiers such as Logistic Regression, Random Forest, SVMs, Gradient Boosted Decision Trees (GBDTs) and Deep Neural Networks(DNNs). The feature spaces for these classifiers are in turn defined by task-specific embeddings learned using three deep learning architectures: FastText, Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs). As baselines, we compare with feature spaces comprising of char n-grams BIBREF0 , TF-IDF vectors, and Bag of Words vectors (BoWV).
Main contributions of our paper are as follows: (1) We investigate the application of deep learning methods for the task of hate speech detection. (2) We explore various tweet semantic embeddings like char n-grams, word Term Frequency-Inverse Document Frequency (TF-IDF) values, Bag of Words Vectors (BoWV) over Global Vectors for Word Representation (GloVe), and task-specific embeddings learned using FastText, CNNs and LSTMs. (3) Our methods beat state-of-the-art methods by a large margin ( INLINEFORM0 18 F1 points better).
In this paper, we experiment with multiple classifiers such as Logistic Regression, Random Forest, SVMs, Gradient Boosted Decision Trees (GBDTs) and Deep Neural Networks(DNNs). 
Answer: experiment with multiple classifier, such as Logistic Regression, Random Forest, Gradient Boosted Decision Trees (GBDTs), Gradient Boosted Decision Trees (GBDTs), Gradient Boosted Decision Trees (GBDTs), Gradient Boosted Decision Trees (GBDTs), Gradient Boosted Decision Trees (GBDTs) and Deep Neural Networks (DNNs).
Question: Which of the following are colors: red, black, yellow, orange, sun, sunflower, chips, book, white, pink, blue, keyboard.
Answer: The colors are: red, black, yellow, orange, white, pink and blue.
Question: What characterizes turbulent flow
Evidence: In fluid dynamics, turbulence or turbulent flow is fluid motion characterized by chaotic changes in pressure and flow velocity. It is in contrast to a laminar flow, which occurs when a fluid flows in parallel layers, with no disruption between those layers.
Answer: Turbulent flow is characterized by chaotic changes in pressure and flow velocity.
Question: Where is Sugarloaf mountain located?
Answer: The Sugarloaf mountain, Pão de Açúcar in Portuguese, is located at the entrance of the Guanabara bay in the city of Rio de Janeiro, capital of the Rio de Janeiro state in Brazil.
Question: Given the following information about the speed of light:
Speed of light in vacuum which has a refractive index of 1 is 300Km/sec
Speed of light in water which has a refractive index of 1.3 is 225Km/sec
Speed of light in diamond which has a refractive index of 2.4 is 125Km/sec

Estimate the speed of light in glass which has a refractive index of 1.5
Answer: From the information given we can see the light of speed is inversely proportional the refractive index of the medium. We can estimate the speed of light in glass as speed of light in vacuum divided by the medium's refractive index. In case of glass that would be 300Km/1.5 = 200Km/sec.

The estimated speed of light in glass will be around 200 Km/sec
Question: Why are children so special?
Answer: Children are incredibly special because they are new to the earth. They have fewer biases and are able to see, imagine and create with perspectives that are unavailable to adults. For example, when a child plays in the sand, she may have only seen or touched sand only twenty times before. For her, the sand holds the promise of new textures, the opportunity to build a yet-unseen creation, and hours of delight before her. The adult sees sand and worries about dirt and bringing sand into the house. The adult has had many experiences with sand and not all of them have been positive. The adult's, vision of sand is clouded by experience. We must hold on and seek out the magic of children so that we can continue to find and enjoy the mysteries of the universe, even if they are not all pleasant every time.
Question: From the passage provided, extract the total corporate debt of Adani group
Evidence: Adani Group is an Indian multinational conglomerate, headquartered in Ahmedabad. It was founded by Gautam Adani in 1988 as a commodity trading business, with the flagship company Adani Enterprises. The Group's diverse businesses include port management, electric power generation and transmission, renewable energy, mining, airport operations, natural gas, food processing and infrastructure.

In April 2021, Adani Group crossed US$100 billion in market capitalization, and in April 2022 it crossed the $200 billion mark, in both cases becoming the third Indian conglomerate to do so, after Tata Group and Reliance Industries. In November 2022, it reached $280 billion (INR 24 trillion) surpassing Tata Group. Adani subsequently lost more than $104 billion of market capitalization after fraud and market manipulation allegations by short-seller firm Hindenburg Research. The Adani Group has also attracted other controversies due to various reports of irregular practices. More than 60 percent of the Adani Group's revenue is derived from coal-related businesses. The company's corporate debt totaled $30 billion in 2022.
Answer: Adani groups corporate debt totaled $30 billion in 2022
Question: what's a scenario in which you see lots of value for CDC ?
Answer: 1. Imagine a very large online service, e.g., Snapchat, keeping user activities in something like MongoDB.  Update rates are very high, the table size is huge, the table footprint is global.
2. You need the data in OLTP because you're trying to use the user data to target ads for them, so storing in Delta is not an option. You need an online solution. This online store maintains aggregates (e.g., clicks over the last 5 min, interest vectors, etc.). Google would use Kansas for this, Facebook uses sharded MySQL + Tao.
3. You need to use this per-user data to analyze your online advertising strategy and re-train your ML models to increase yield.
4. You cannot hit the serving DB with analytical workloads, they're not optimized for that. Many no-SQL DB's don't even allow the kinds of queries you need to run.
5. The database is very large, so taking a snapshot is expensive and slow.
6. A lot of users are inactive at any specific time of the day, so snapshotting the entire state is also inefficient.
7. I want to also know changes in the original production DB. The production DB is an OLTP store and cannot keep that much state.
CDC --- can be an effective answer for this use case.
Question: Before Miley Cyrus recorded "Wrecking Ball," it was offered to which singer?
Answer: Beyonce.
Question: What was Hurricane Ian?
Answer: Hurricane Ian was a powerful Atlantic hurricane which was the third-costliest weather disaster on record, and the deadliest hurricane to strike the state of Florida since the 1935 Labor Day hurricane. Ian caused widespread damage across western Cuba and the southeast United States, especially the states of Florida, South Carolina, and North Carolina. It was the ninth named storm, fourth hurricane, and second major hurricane of the 2022 Atlantic hurricane season. Ian was the strongest hurricane to hit the state since Hurricane Michael in 2018, the most recent major hurricane to strike the west coast of Florida since Hurricane Irma in 2017, the first Category 5 hurricane in the Atlantic since Hurricane Lorenzo of 2019, and the strongest Category 4 hurricane to hit the region since Hurricane Charley in 2004, which made a near identical landfall.
Question: In YAML tell me a list of teams mentioned in the text. It should be in the form `location: ${location}`, `mascot: ${mascot}`
Evidence: The Dallas Cowboys joined the NFL as an expansion team in 1960. The team's national following might best be represented by its NFL record of consecutive sell-outs. The Cowboys' streak of 190 consecutive sold-out regular and post-season games (home and away) began in 2002. The franchise has made it to the Super Bowl eight times, tying it with the Pittsburgh Steelers and Denver Broncos for second-most Super Bowl appearances in history behind the New England Patriots' record 11 appearances. The Cowboys have won eight NFC championships, the most in the conference's history. The Cowboys are the only NFL team to record 20 straight winning seasons (from 1966 to 1985) during which they missed the playoffs only twice (1974 and 1984).
Answer: - location: Dallas
  mascot: Cowboys
- location: Pittsburgh
  mascot: Steelers
- location: Denver
  mascot: Broncos
- location: New England
  mascot: Patriots
Question: What is the training objective of their pair-to-sequence model?
Evidence: The training objective is to minimize the negative likelihood of the aligned unanswerable question $\tilde{q}$ given the answerable question $q$ and its corresponding paragraph $p$ that contains the answer $a$ : L=-(q,q,p,a)DP(q|q,p,a;) where $\mathcal {D}$ is the training corpus and $\theta $ denotes all the parameters. Sequence-to-sequence and pair-to-sequence models are trained with the same objective.
The training objective is to minimize the negative likelihood of the aligned unanswerable question $\tilde{q}$ given the answerable question $q$ and its corresponding paragraph $p$ that contains the answer $a$ : L=-(q,q,p,a)DP(q|q,p,a;) where $\mathcal {D}$ is the training corpus and $\theta $ denotes all the parameters. Sequence-to-sequence and pair-to-sequence models are trained with the same objective.
Answer: The answers are shown as follows:
* is to minimize the negative likelihood of the aligned unanswerable question $\tilde{q}$ given the answerable question $q$ and its corresponding paragraph $p$ that contains the answer
Question: Give me a bullet list of 5 US states that have a coastline with the Pacific Ocean
Answer: - California
- Oregon
- Washington
- Alaska
- Hawaii
Question: Tell me if these are safe or not safe to let me child play with: the monkey bars, matches, scissors, rock paper scissors, a baseball, the stove, a cooking board game
Answer: the monkey bars: safe, matches: not safe, scissors: not safe, rock paper scissors: safe, a baseball: safe, the stove: not safe, a cooking board game: safe
Question: Is water wet?
Answer: When water comes into direct contact with other things, the other things become wet. Water  as we experience it is not a singular entity, rather a collection of a large number of water molecules. The water molecules touch other water molecules, and as previously established, when water touches other things, the other things become wet. Therefore, because there is a point of contact between water molecules (a strong polar bond in this case), water is wet.
Question: What parallel corpus did they use?
Evidence: In this section, we present the experimental settings for pointer-generator network and language model. Our experiment, our pointer-generator model has 500-dimensional hidden states and word embeddings. We use 50k words as our vocabulary for source and target. We evaluate our pointer-generator performance using BLEU score. We take the best model as our generator and during the decoding stage, we generate 1-best and 3-best using beam search with a beam size of 5. For the input, we build a parallel monolingual corpus by translating the mixed language sequence using Google NMT to English ( INLINEFORM0 ) and Mandarin ( INLINEFORM1 ) sequences. Then, we concatenate the translated English and Mandarin sequences and assign code-switching sequences as the labels ( INLINEFORM2 ).
For the input, we build a parallel monolingual corpus by translating the mixed language sequence using Google NMT to English ( INLINEFORM0 ) and Mandarin ( INLINEFORM1 ) sequences.
Answer: Parallel monolingual corpus in English and Mandarin
Question: What awards did Zach Edey win?
Evidence: On December 17, 2022, Edey became both the 55th player in Purdue's history to reach 1,000 career points and the 11th player in Purdue's history to reach 100 career blocks.

During the 2022-23 season, Edey received Big Ten Player of the Week six times, tying the school record for most awards in a single season (Caleb Swanigan, 2016-17) and rising to second most all-time in men's basketball in the Big Ten (Evan Turner, 2010-11).

At the close of the season, Edey was named the Big Ten Player of the Year and Sporting News National Player of the Year. He was also named a consensus first-team All-American.
Answer: Zach Edey won the following awards:
- Big Ten Player of the Week (6x)
- Big Ten Player of the Year
- Sporting News National Player of the Year
- consensus first-team All-American
Question: Does the training on more rounds improve model performance?
Evidence: Table TABREF13 reports the main results. In addition to BERT BIBREF10 and RoBERTa BIBREF25, we also include XLNet BIBREF30 as an example of a strong, but different, model architecture. We show test set performance on the ANLI test sets per round, the total ANLI test set, and the exclusive test subset (examples from test-set-exclusive workers). We also show accuracy on the SNLI test set and the MNLI development (for the purpose of comparing between different model configurations across table rows) set. In what follows, we briefly discuss our observations.
Generally, our results indicate that training on more rounds improves model performance.
Answer: Yes, it does.
Question: What is a Delta Lake?
Answer: A Delta Lake is an open-source storage layer designed to run on top of an existing data lake and improve its reliability, security, and performance. Delta Lakes support ACID transactions, scalable metadata, unified streaming, and batch data processing.
Question: Tell me three ways to get coconut from a coconut tree
Answer: Here are the three ways to get coconut from a coconut tree
1) Using a pole and saw:
Attach a curved saw to end of a very long stick. Make sure the saw does not fall when you pull on the coconut.Stand away from the bottom of the tree at a safe distance and hook the saw on to the stem of the coconut and pull down. 

2) Using foot strap to climb:
Make a foot strap out of a cloth or a rope and climb on the coconut tree by gripping the tree with your hand and the knot on your legs. Make sure the loop around your feet is stretched tight against the tree. Once you reach the top of the tree, you can cut a coconut with a knife that you carried on your belt

3) Using a ladder to climb:
This method is useful for shorter coconut trees. Keep the ladder slanting against the coconut tree on a stable ground. Make sure the ladder is stable while you climb. Climb up the ladder and once you can reach the coconut, cut it out with a knife.
Question: Give me a list of your favor pet and breeds
Answer: My favor cat breed is Ragdoll. My favor Dog breed is Shiba Inu
Question: What is salvation in christianity?
Evidence: In Christianity, salvation (also called deliverance or redemption) is the "saving  human beings from sin and its consequences, which include death and separation from God" by Christ's death and resurrection, and the justification following this salvation.

While the idea of Jesus' death as an atonement for human sin was recorded in the Christian Bible, and was elaborated in Paul's epistles and in the Gospels, Paul saw the faithful redeemed by participation in Jesus' death and rising. Early Christians regarded themselves as partaking in a new covenant with God, open to both Jews and Gentiles, through the sacrificial death and subsequent exaltation of Jesus Christ. Early Christian notions of the person and sacrificial role of Jesus in human salvation were further elaborated by the Church Fathers, medieval writers and modern scholars in various atonement theories, such as the ransom theory, Christus Victor theory, recapitulation theory, satisfaction theory, penal substitution theory and moral influence theory.

Variant views on salvation (soteriology) are among the main fault lines dividing the various Christian denominations, including conflicting definitions of sin and depravity (the sinful nature of mankind), justification (God's means of removing the consequences of sin), and atonement (the forgiving or pardoning of sin through the suffering, death and resurrection of Jesus).
Answer: Salvation in christianity is the redemption of human beings from the consequences of their sins through the death and resurrection of Jesus Christ. Jesus's death is counted as the payment for the sin of all mankind, as recorded by Paul in his letters. This salvation is open to everyone, not just the jews. Anyone who believes that Jesus died for their sins and rose again receives the salvation that God has to offer.
Question: Identify which animal species is alive or extinct: Maiasaura, Sea Lions
Answer: Sea Lions are alive, Maiasaura is extinct.
Question: What are the benefits of meditation?
Answer: Meditation enhances focus, memory, and mood. Meditation has also been shown to have other benefits such as reducing the negative impacts of lack of sleep.