DataHammer/scimrc huggingface dataset:
Question: What is a narcissist?
Answer: People who see themselves as the center of the universe. Narcissists gain confidence by putting others down. They feel attacked at the slightest thing, even when a comment has nothing to do with them. They're small human beings. They lack grace, wisdom, humility, integrity, and perhaps even a conscience. Narcissists make the worst mothers — traumatizing their children, feeling resentful and jealous of their children and in the worst cases, seeing their daughters as their competition. Narcissists make the worst kind of boss. Unfortunately, many narcissists are in positions of power.
Question: What would Bruce lee do if he is alive?
Answer: Bruce Lee is an American martial artist, actor and philosopher. He is born on November 27, 1940. If Bruce Lee is alive today he would be 83 years old, and he would be happily retired and probably suffering from Alzheimer's
Question: Give me some places to visit with a 8 year old kid
Answer: Here are some places you can take a 8 year old kid
Zoos
Parks
Beaches
Aquarium
Museums
Short hiking trails
Amusement parks
Trampoline parks
Restaurants with indoor play area
Arcade
Lazer tag
Library
Bowling
Paint ball
Question: Explain pickball
Evidence: Pickleball is an indoor or outdoor racket/paddle sport where two players (singles), or four players (doubles), hit a perforated hollow plastic ball over a 36-inch-high (0.91 m) net using solid-faced paddles. Opponents on either side of the net hit the ball back and forth until one side commits a rule infraction. Pickleball was invented in 1965 as a children's backyard game on Bainbridge Island, Washington, US. In 2022, pickleball was adopted as the official state sport of Washington.
Answer: Pickleball can be played both inside or outside. It's played with two or four placers and players. Players hit a hallow ball over a 36 inch net. Players hit back and forth until one side hits the ball out of bounce or not over the net.
Question: What commands does their setup provide to models seeking information?
Evidence: Information Gathering: At step $t$ of the information gathering phase, the agent can issue one of the following four actions to interact with the paragraph $p$, where $p$ consists of $n$ sentences and where the current observation corresponds to sentence $s_k,~1 \le k \le n$:
previous: jump to $ \small {\left\lbrace \begin{array}{ll} s_n & \text{if $k = 1$,}\\ s_{k-1} & \text{otherwise;} \end{array}\right.} $
next: jump to $ \small {\left\lbrace \begin{array}{ll} s_1 & \text{if $k = n$,}\\ s_{k+1} & \text{otherwise;} \end{array}\right.} $
Ctrl+F $<$query$>$: jump to the sentence that contains the next occurrence of “query”;
stop: terminate information gathering phase.
Information Gathering: At step $t$ of the information gathering phase, the agent can issue one of the following four actions to interact with the paragraph $p$, where $p$ consists of $n$ sentences and where the current observation corresponds to sentence $s_k,~1 \le k \le n$:

previous: jump to $ \small {\left\lbrace \begin{array}{ll} s_n & \text{if $k = 1$,}\\ s_{k-1} & \text{otherwise;} \end{array}\right.} $

next: jump to $ \small {\left\lbrace \begin{array}{ll} s_1 & \text{if $k = n$,}\\ s_{k+1} & \text{otherwise;} \end{array}\right.} $

Ctrl+F $<$query$>$: jump to the sentence that contains the next occurrence of “query”;

stop: terminate information gathering phase.
Answer: The answers are shown as follows:
* previous
* next
* Ctrl+F $<$query$>$
* stop
Question: How many cycling world championships has Peter Sagan won?
Evidence: Sagan is considered one of cycling's greatest talents, having earned many prestigious victories, including three consecutive World Championships, one European Championship, two Paris–Nice stages, seven Tirreno–Adriatico stages, one in the Tour de Romandie, three and the overall classification in the Tour de Pologne, a record seventeen stages and the overall in the Tour of California, and another fifteen in the Tour de Suisse.
Answer: Sagan has won three consecutive cycling world championships
Question: What Are Some Good Ideas for a YouTube Channel?
Answer: Personal Vlog, Education, Travelling, Comedy, Film/TV Reviews, Personal Finance
Question: What is the best way to prep concrete before applying epoxy?
Answer: There are several ways to prepare concrete before applying an epoxy coating. Preparation ensures that the appropriate texture has been introduced to the top layer of the concrete and helps the epoxy to bond with the concrete better. This ensures long-lasting results. All of these different methods of preparing concrete vary in terms of the level of difficulty as well as the efficacy produced. Following are the most popular techniques:

1. Acid Etching: This is the most DIY friendly option & involves the use of an acid that is allowed to rest for some time over the concrete surface and then cleaned after a few minutes. This is also the quickest among all the techniques. The downside however is that the etching process may not produce the best concrete texture that ensures a long-lasting bond. 
2. Walk-behind Concrete Diamond grinder: This produces one of the best results when compared to the other techniques. It involves the use of a walk behind concrete grinder which has been fitted with a diamond grinding attachment. The disadvantage of this method is that it requires specialized equipment which may not be readily available & is a lot more time consuming compared to Acid etching.
3. Hand Grinder with Diamond Cup Wheel: This is the most accessible option that yields results that are equivalent to using a walk-behind concrete grinder. The only drawback of this approach is that this is the most time consuming compared to other methods and is only practical for covering small areas.
Question: Who was the first Time Magazine Man of the Year?
Answer: Charles Lindbergh was named Time Magazine's Man of the Year in 1927.
Question: What are the main use cases for AWS Kinesis?
Answer: Some of the main use cases for AWS Kinesis are:
1. Real-time Data Streaming and Processing
2. Log Aggregation and Data Pipeline
3. Messaging and Notification Services
4. Metrics and Monitoring
5. Data Integration and ETL
6. CDC Events Ingestion
7. Clickstream Data Analysis
8. Fraud Detection and Security
9. Recommendation Systems
10. Internet of Things (IoT) Data Ingestion
Question: What was the primary mode of transportation across the San Francisco bay prior to the Golden Gate Bridge?
Evidence: Before the bridge was built, the only practical short route between San Francisco and what is now Marin County was by boat across a section of San Francisco Bay. A ferry service began as early as 1820, with a regularly scheduled service beginning in the 1840s for the purpose of transporting water to San Francisco.

The Sausalito Land and Ferry Company service, launched in 1867, eventually became the Golden Gate Ferry Company, a Southern Pacific Railroad subsidiary, the largest ferry operation in the world by the late 1920s. Once for railroad passengers and customers only, Southern Pacific's automobile ferries became very profitable and important to the regional economy. The ferry crossing between the Hyde Street Pier in San Francisco and Sausalito Ferry Terminal in Marin County took approximately 20 minutes and cost $1.00 per vehicle,[when?] a price later reduced to compete with the new bridge. The trip from the San Francisco Ferry Building took 27 minutes.
Answer: The only (practical) way to get across the San Francisco Bay prior to 1937 was by Ferry. The Golden Gate Ferry Company, which became the largest ferry operation by the late 1920's, was established in 1867 as the Sausalito Land & Ferry Company. The ferry would take approximately 20 minutes and cost $1.00 per vehicle.
Question: Which of these are both movies and books: Harry Potter, Lord of the Rings, Brave World, The Shawshank Redemption.
Answer: Harry Potter and Lord of the Rings were adapted to movies from books.
Question: What is Braising?
Answer: Braising is a combination cooking method that starts with a pan searing then followed by a slow cooking in a liquid until the ingredients become tender.  Braising technique can be used on all cuts of meats or vegetables, but is especially with tougher cuts of meat like briskets.  Braising can be performed slowly for hours in a pot or oven to allow for flavors to penetrate.  Braising can also be done in minutes in a pressure cooker (Intsta Pot).
Question: How much better peformance is achieved in human evaluation when model is trained considering proposed metric?
Evidence: The experimental results are summarized in Table 1. We can see that the proposed comparative evaluator correlates far better with human judgment than BLEU and perplexity. When compared with recently proposed parameterized metrics including adversarial evaluator and ADEM, our model consistently outperforms them by a large margin, which demonstrates that our comparison-based evaluation metric is able to evaluate sample quality more accurately. In addition, we find that evaluating generated samples by comparing it with a set of randomly selected samples or using sample-level skill rating performs almost equally well. This is not surprising as the employed skill rating is able to handle the inherent variance of players (i.e. NLG models). As this variance does not exist when we regard a sample as a model which always generates the same sample.
Results are shown in Table 2. We can see that the proposed comparative evaluator with skill rating significantly outperforms all compared baselines, including comparative evaluator with averaged sample-level scores. This demonstrates the effectiveness of the skill rating system for performing model-level comparison with pairwise sample-level evaluation. In addition, the poor correlation between conventional evaluation metrics including BLEU and perplexity demonstrates the necessity of better automated evaluation metrics in open domain NLG evaluation.
FLOAT SELECTED: Table 1: Sample-level correlation between metrics and human judgments, with p-values shown in brackets.
FLOAT SELECTED: Table 2: Model-level correlation between metrics and human judgments, with p-values shown in brackets.
The experimental results are summarized in Table 1. We can see that the proposed comparative evaluator correlates far better with human judgment than BLEU and perplexity.
Results are shown in Table 2. We can see that the proposed comparative evaluator with skill rating significantly outperforms all compared baselines, including comparative evaluator with averaged sample-level scores.
FLOAT SELECTED: Table 1: Sample-level correlation between metrics and human judgments, with p-values shown in brackets.
FLOAT SELECTED: Table 2: Model-level correlation between metrics and human judgments, with p-values shown in brackets.
Answer: Pearson correlation to human judgement - proposed vs next best metric
Sample level comparison:
- Story generation: 0.387 vs 0.148
- Dialogue: 0.472 vs 0.341
Model level comparison:
- Story generation:  0.631 vs 0.302
- Dialogue: 0.783 vs 0.553
Question: Does the neural model for extracting parallel sentences use a large dataset to learn?
Evidence: Both neural and statistical machine translation approaches are highly reliant on the availability of large amounts of data and are known to perform poorly in low resource settings. Recent crowd-sourcing efforts and workshops on machine translation have resulted in small amounts of parallel texts for building viable machine translation systems for low-resource pairs BIBREF0 . But, they have been shown to suffer from low accuracy (incorrect translation) and low coverage (high out-of-vocabulary rates), due to insufficient training data. In this project, we try to address the high OOV rates in low-resource machine translation systems by leveraging the increasing amount of multilingual content available on the Internet for enriching the bilingual lexicon.
Comparable corpora such as Wikipedia, are collections of topic-aligned but non-sentence-aligned multilingual documents which are rich resources for extracting parallel sentences from. For example, Figure FIGREF1 shows that there are equivalent sentences on the page about Donald Trump in Tamil and English, and the phrase alignment for an example sentence is shown in Table TABREF4 .
Table TABREF2 shows that there are at least tens of thousands of bilingual articles on Wikipedia which could potentially have at least as many parallel sentences that could be mined to address the scarcity of parallel sentences as indicated in column 2 which shows the number of sentence-pairs in the largest available bilingual corpora for xx-en. As shown by BIBREF1 ( BIBREF1 ), the illustrated data sparsity can be addressed by extending the scarce parallel sentence-pairs with those automatically extracted from Wikipedia and thereby improving the performance of statistical machine translation systems.
In this paper, we will propose a neural approach to parallel sentence extraction and compare the BLEU scores of machine translation systems with and without the use of the extracted sentence pairs to justify the effectiveness of this method. Compared to previous approaches which require specialized meta-data from document structure or significant amount of hand-engineered features, the neural model for extracting parallel sentences is learned end-to-end using only a small bootstrap set of parallel sentence pairs.
Compared to previous approaches which require specialized meta-data from document structure or significant amount of hand-engineered features, the neural model for extracting parallel sentences is learned end-to-end using only a small bootstrap set of parallel sentence pairs.
Answer: No.
Question: What is a security in finance?
Answer: A security is a tradable financial asset. The term commonly refers to any form of financial instrument, but its legal definition varies by jurisdiction. In some countries and languages people commonly use the term "security" to refer to any form of financial instrument, even though the underlying legal and regulatory regime may not have such a broad definition. In some jurisdictions the term specifically excludes financial instruments other than equities and Fixed income instruments. In some jurisdictions it includes some instruments that are close to equities and fixed income, e.g., equity warrants.

Securities may be represented by a certificate or, more typically, they may be "non-certificated", that is in electronic (dematerialized) or "book entry only" form. Certificates may be bearer, meaning they entitle the holder to rights under the security merely by holding the security, or registered, meaning they entitle the holder to rights only if they appear on a security register maintained by the issuer or an intermediary. They include shares of corporate stock or mutual funds, bonds issued by corporations or governmental agencies, stock options or other options, limited partnership units, and various other formal investment instruments that are negotiable and fungible.
Question: Classify each of the following as either a country or a city: Sweden, France, Paris, Bali, Rotterdam, Seville, India, San Fransisco, Amritsar, Portugal
Answer: Countries: Sweden, France, India, Portugal
Cities: Paris, Bali, Rotterdam,Seville,San Fransisco, Amritsar
Question: Identify which instrument is string or percussion: Dollu, Tidinet
Answer: Tidinet is string, Dollu is percussion.
Question: Identify which instrument is string or percussion: Sambal, Yueqin
Answer: Yueqin is string, Sambal is percussion.
Question: The shallow syntax is not particularly helpful when using CWRs, is that right?
Evidence: Our experiments evaluate the effect of shallow syntax, via contextualization (mSynC, §SECREF2) and features (§SECREF3). We provide comparisons with four baselines—ELMo-transformer BIBREF0, our reimplementation of the same, as well as two cwr-free baselines, with and without shallow syntactic features. Both ELMo-transformer and mSynC are trained on the 1B word benchmark corpus BIBREF19; the latter also employs chunk annotations (§SECREF2). Experimental settings are detailed in Appendix §SECREF22.
Overall, the performance differences across all tasks are small enough to infer that shallow syntax is not particularly helpful when using CWRs.
Answer: Yes, this is inferred by the performance differences across all tasks are small enough.
Question: Why do Filipinos like eating rice so much?
Answer: Well, that has to do with the fact that the Filipino soil is ideal for rice cultivation. Also, given that rice is produced in abundance in the Phillipines, it becomes cheaper than other food staples. Therefore, rice easily became the most common dish in an ordinary Filipino household.
One can also say, that the neutral nature of rice flavour parries well with the Filipino traditional dishes like Adobo, Sinigang and Kare-Kare which are rich in flavour and welcome more neutral side dishes
Question: What are the qualities of good compost for a vegetable garden?
Answer: Compost can be added to the soil in a vegetable garden. Positive qualities of good compost for growing vegetables include absorbency and soluble minerals. Good compost will hold an appropriate amount of moisture and contain a mix of minerals that are bioavailable for the plants in the garden.
Question: Name some of the best overall philosophical books
Answer: Meditations by Marcus Aurelius.
Man's Search for Meaning by Viktor Frankl.
The Daily Stoic by Ryan Holiday.
The Story of Philosophy by Will Durant.
The Republic by Plato.
Discourses by Epictetus.
The Last Lecture by Randy Pausch.
Letters from a Stoic by Seneca.
Question: Classify each of the following as either a title by Kevin Kwan or Veronica Roth: Sex and Vanity, Crazy Rich Asians, China Rich Girlfriend, Rich People Problems, Luck: The Essential Guide, Divergent, Allegiant, Insurgent, Carve the Mark, Chosen Ones
Answer: Kevin Kwan: Sex and Vanity, Crazy Rich Asians, China Rich Girlfriend, Rich People Problems, Luck: The Essential Guide
Veronica Roth: Divergent, Allegiant, Insurgent, Carve the Mark, Chosen Ones
Question: separate the following into chilldrens and adults cartoons.
recess
rugrats
big mouth
swat cats
inside job
popeyes
dexters lab
king of the hill
south park
Answer: childrens cartoons: recess, rugrats, swat cats, popeyes, dexters lab

adult cartoons: big mouth, inside job, king of the hill, south park
Question: What are the primary causes of inflation?
Answer: It is common for currency value to decline when the amount of money in an economy (the money supply) increases too rapidly.
Most economists believe an increased money supply monetary inflation causes the price of goods and services to increase over a longer period of time. However, they disagree on causes over a shorter period of time.
Question: What is the name of Dorothy's dog?
Answer: Dorothy's dog is named Toto
Question: Identify the bird from the list: Not, Knot, Nought
Answer: Knot
Question: Who invented the airplane?
Answer: The airplane was invented by Santos Dumont, a Brazilian inventor. He flew for the first time in France, in the year of 1906.
Question: How should I go about planning a trip to Europe?
Answer: Planning a trip to Europe is similar to planning any travel in some ways but quite different in others. This is because Europe is a diverse continent made up of countries each with their unique culture, geography and climate. Moreover, every country has something unique to offer by way of things to do. Therefore, while planning your trip to Europe, first consider what kind of experience you want, for example, whether you want a more modern holiday or a rustic vacation, whether you want to spend time on the beach or rather partake in winter sports or activities. Consider also whether you like warmer climates or enjoy winter weather. Once you have established that, consider your budget and for how any days you can travel. After you decide on all those parameters, you can create your travel itinerary and either do your travel booking yourself or approach a travel agent to do it for you.
Question: What does the team consider as a good way to check a dataset collection' s balance and representativeness?
Evidence: Sometimes all we have is documents, but often we want to look at documents in the context of some additional information, or metadata. This additional information could tell us about the creation of documents (date, author, forum), or about the reception of documents (flagged as hate speech, helpful review). Information about text segments can be extremely valuable, but it is also prone to errors, inconsistencies, bias, and missing information. Examining metadata is a good way to check a collection's balance and representativeness. Are sources disproportionately of one form? Is the collection missing a specific time window? This type of curation can be extremely time consuming as it may require expert labeling, but it often leads to the most compelling results. Sometimes metadata are also used as target labels to develop machine learning models. But using them as a “ground truth” requires caution. Labels sometimes mean something different than we expect. For example, a down vote for a social media post could indicate that the content is offensive, or that the voter simply disagreed with the expressed view.
Examining metadata is a good way to check a collection’s balance and representativeness.
Answer: Examining metadata.
Question: Tell me if these are toppings for pizza: pepperoni, cheese, sausage, peppers, onions, bacon, mushrooms, pineapple
Answer: When it comes to pizza toppings, there are some long and fast rules.  Meats are universally accepted to pepperoni, sausage, and bacon are confirmed toppings for pizza.  Vegetables are also universally accepted as pizza toppings While personal tastes in vegetables vary and not everyone enjoys mushrooms, the fitment is unquestioned. Pineapple is likely the most controversial topic when it comes to pizza toppings and whether it applies.
Question: What are the stated main reasons the iAPX432 architecture failed?
Evidence: Using the semiconductor technology of its day, Intel's engineers weren't able to translate the design into a very efficient first implementation. Along with the lack of optimization in a premature Ada compiler, this contributed to rather slow but expensive computer systems, performing typical benchmarks at roughly 1/4 the speed of the new 80286 chip at the same clock frequency (in early 1982). This initial performance gap to the rather low-profile and low-priced 8086 line was probably the main reason why Intel's plan to replace the latter (later known as x86) with the iAPX 432 failed. Although engineers saw ways to improve a next generation design, the iAPX 432 capability architecture had now started to be regarded more as an implementation overhead rather than as the simplifying support it was intended to be
Answer: The many features included resulted in a very complex processor that was difficult to manufacture. The complexity also resulted in a very slow and expensive processor which was not competitive in the market. The initial failure cast doubt on the entire approach taken to develop a new architecture, making further iterations to improve the processor more difficult.
Question: During which decade did neural networks first lead to practically useful systems?
Evidence: The development of metal–oxide–semiconductor (MOS) very-large-scale integration (VLSI), in the form of complementary MOS (CMOS) technology, enabled increasing MOS transistor counts in digital electronics. This provided more processing power for the development of practical artificial neural networks in the 1980s. From 1988 onward, the use of neural networks transformed the field of protein structure prediction, in particular when the first cascading networks were trained on profiles (matrices) produced by multiple sequence alignments.
Answer: The development of metal–oxide–semiconductor (MOS) very-large-scale integration (VLSI), in the form of complementary MOS (CMOS) technology, enabled the development of practical artificial neural networks in the 1980s