DataHammer/scimrc huggingface dataset:
Question: What kind of merchant ships would be useful in a modern naval conflict?
Answer: Two broad categories of merchant ships would likely be most useful in a modern naval conflict: large roll-on/roll-off ships with double hulls and small, fast ferries. If an adversary can find a ship on the open ocean and target it with a modern anti-ship missile, this opponent can certainly destroy the complex machinery needed to operate a container port or an oil terminal. Consequently, any cargo you want to unload in a war zone is going to need to drive off a ship on the back of a truck....quickly. An oil tanker will be useless, but a RO/RO ship loaded with tanker trucks can unload lots of fuel under austere/wartime conditions. Similarly, a container ship will be of little use without the large, land-based cranes used at most container shipping ports. A ferry loaded with trucks hauling shipping containers can quickly load and unload without the need for specialized equipment. Data from the Iran-Iraq war suggest that a large, 50,000+ ton RO/RO with a double hull is likely big enough to survive a hit from a modern anti-ship missile. A fast ferry that can move at ~40 knots is probably going to be too small to detect from space or shore using backscatter radar. Conversely, a 100,000-ton PanMax oil tanker or a 5,000 TEU container ship will be easy to detect, and slow enough to target.
Question: Give me Personal finance advice
Answer: Live within your means. 
Save and Invest 
Avoid credit cards
Avoid any financial product that you don't understand
Do research before making a large purchase
Read financial books and blogs to get educated on personal finance
Home ownership generally is worth more in the long run
Ensure you have sufficient insurance to cover unexpected major catastrophes
Question: In which languages did the approach outperform the reported results?
Evidence: In BIBREF3 , BIBREF2 , the authors study the effect of translation in sentiment classifiers; they found better to use native Arabic speakers as annotators than fine-tuned translators plus fine-tuned English sentiment classifiers. In BIBREF21 , the idea is to measure the effect of the agreement among annotators on the production of a sentiment-analysis corpus. Both, on the technical side, both papers use fine tuned classifiers plus a variety of pre-processing techniques to prove their claims. Table TABREF24 supports the idea of choosing B4MSA as a bootstrapping sentiment classifier because, in the overall, B4MSA reaches superior performances regardless of the language. Our approach achieves those performance's levels since it optimizes a set of parameters carefully selected to work on a variety of languages and being robust to informal writing. The latter problem is not properly tackled in many cases.
FLOAT SELECTED: Table 5: Performance on multilingual sentiment analysis (not challenges). B4MSA was restricted to use only the multilingual set of parameters.
Table TABREF24 supports the idea of choosing B4MSA as a bootstrapping sentiment classifier because, in the overall, B4MSA reaches superior performances regardless of the language.
FLOAT SELECTED: Table 5: Performance on multilingual sentiment analysis (not challenges). B4MSA was restricted to use only the multilingual set of parameters.
Answer: Arabic, German, Portuguese, Russian, Swedish
Question: Given a reference tax about a footballer, tell me when they were born, what is their nationalities and which years they won the FIFA World cup.
Evidence: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an Argentine professional footballer who plays as a forward for Ligue 1 club Paris Saint-Germain and captains the Argentina national team. Widely regarded as one of the greatest players of all time, Messi has won a record seven Ballon d'Or awards[note 2] and a record six European Golden Shoes, and in 2020 he was named to the Ballon d'Or Dream Team. Until leaving the club in 2021, he had spent his entire professional career with Barcelona, where he won a club-record 34 trophies, including 10 La Liga titles, seven Copa del Rey titles and four UEFA Champions Leagues. With his country, he won the 2021 Copa América and the 2022 FIFA World Cup. A prolific goalscorer and creative playmaker, Messi holds the records for most goals in La Liga (474), most hat-tricks in La Liga (36) and the UEFA Champions League (eight), and most assists in La Liga (192) and the Copa América (17). He also has the most international goals by a South American male (102). Messi has scored over 800 senior career goals for club and country, and has the most goals by a player for a single club (672).
Answer: Lionel Andrés Messi, also known as Leo Messi, was born 24 June 1987. He is an Argentine professional footballer. In 2022, He won 2022 FIFA World Cup with his country.
Question: Is there any explanation why some choice of language pair is better than the other?
Evidence: Zero-shot transfer using multilingual BERT performs poorly when transferring to Japanese on the MedWeb data. However, training on machine translations gives promising performance, and this performance can be increased by adding small amounts of original target data. On inspection, the drop in performance between translated and original Japanese was often a result of translations that were reasonable but not consistent with the labels. For example, when translating the first example in Figure FIGREF2, both machine translations map “UTF8min風邪”, which means cold (the illness), into “UTF8min寒さ”, which means cold (low temperature). Another example is where the Japanese pseudo-tweet “UTF8min花粉症の時期はすごい疲れる。” was provided alongside an English pseudo-tweet “Allergy season is so exhausting.”. Here, the Japanese word for hay fever “UTF8min花粉症。” has been manually mapped to the less specific word “allergies” in English; the machine translation maps back to Japanese using the word for “allergies” i.e. “UTF8minアレルギー” in the katakana alphabet (katakana is used to express words derived from foreign languages), since there is no kanji character for the concept of allergies. In future work, it would be interesting to understand how to detect such ambiguities in order to best deploy our annotation budget.
On inspection, the drop in performance between translated and original Japanese was often a result of translations that were reasonable but not consistent with the labels. For example, when translating the first example in Figure FIGREF2, both machine translations map “UTF8min風邪”, which means cold (the illness), into “UTF8min寒さ”, which means cold (low temperature). Another example is where the Japanese pseudo-tweet “UTF8min花粉症の時期はすごい疲れる。” was provided alongside an English pseudo-tweet “Allergy season is so exhausting.”. Here, the Japanese word for hay fever “UTF8min花粉症。” has been manually mapped to the less specific word “allergies” in English; the machine translation maps back to Japanese using the word for “allergies” i.e. “UTF8minアレルギー” in the katakana alphabet (katakana is used to express words derived from foreign languages), since there is no kanji character for the concept of allergies.
Answer: The answers are shown as follows:
* translations that were reasonable but not consistent with the labels
Question: In the smaller Jasper5x3 model experiment, which setting performs best?
Evidence: In our study, we evaluate performance of models with:
3 types of normalization: batch norm BIBREF10 , weight norm BIBREF9 , and layer norm BIBREF17 
3 types of rectified linear units: ReLU, clipped ReLU (cReLU), and leaky ReLU (lReLU)
2 types of gated units: gated linear units (GLU) BIBREF8 , and gated activation units (GAU) BIBREF18 
All experiment results are shown in Table TABREF15 . We first experimented with a smaller Jasper5x3 model to pick the top 3 settings before training on larger Jasper models. We found that layer norm with GAU performed the best on the smaller model. Layer norm with ReLU and batch norm with ReLU came second and third in our tests. Using these 3, we conducted further experiments on a larger Jasper10x4. For larger models, we noticed that batch norm with ReLU outperformed other choices. Thus, leading us to decide on batch normalization and ReLU for our architecture.
During batching, all sequences are padded to match the longest sequence. These padded values caused issues when using layer norm. We applied a sequence mask to exclude padding values from the mean and variance calculation. Further, we computed mean and variance over both the time dimension and channels similar to the sequence-wise normalization proposed by Laurent et al. BIBREF19 . In addition to masking layer norm, we additionally applied masking prior to the convolution operation, and masking the mean and variance calculation in batch norm. These results are shown in Table TABREF16 . Interestingly, we found that while masking before convolution gives a lower WER, using masks for both convolutions and batch norm results in worse performance.
As a final note, we found that training with weight norm was very unstable leading to exploding activations.
All experiment results are shown in Table 2. We first experimented with a smaller Jasper5x33 model to pick the top 3 settings before training on larger Jasper models. We found that layer norm with GAU performed the best on the smaller model.
Answer: Layer norm with GAU.
Question: Tell me whether these are tree nuts: coconut, walnut, nutmeg, peanut, sesame, cashew, macadamia, almond.
Answer: Walnut, cashew, macadamia, and almond are classified as tree nuts. Nutmeg, peanut, and sesame are not. Coconut is recognized by some government and health organizations as a tree nut, however it is botanically classified as a fruit.
Question: Classify below into more useful and less useful minerals in our food: iron, calcium, magnesium, chloride, selenium, potassium, phosphorous,  zinc, iodine, mercury, copper.
Answer: In the given minerals, these are the minerals more useful to have in our foods: magnesium, sodium, calcium, phosphorous, chloride and potassium.
In the given minerals, these are the minerals less useful to have in our foods: iron, iodine, zinc, selenium, copper and mercury
Question: What is House of the Dragon?
Evidence: House of the Dragon is an American fantasy drama television series created by George R. R. Martin and Ryan Condal for HBO. A prequel to Game of Thrones (2011–2019), it is the second television series in the A Song of Ice and Fire franchise. Condal and Miguel Sapochnik served as the showrunners for the first season. Based on Martin's 2018 novel Fire & Blood, the series is set about 100 years after the Seven Kingdoms are united by the Targaryen Conquest, nearly 200 years before the events of Game of Thrones, and 172 years before the birth of Daenerys Targaryen. Featuring an ensemble cast, the show portrays the events leading up to the beginning of the decline of House Targaryen, a devastating war of succession known as the "Dance of the Dragons".
Answer: House of the Dragon is an American fantasy drama television series created by George R. R. Martin and Ryan Condal for HBO. A prequel to Game of Thrones (2011–2019), it is the second television series in the A Song of Ice and Fire franchise. Condal and Miguel Sapochnik served as the showrunners for the first season. Based on Martin's 2018 novel Fire & Blood, the series is set about 100 years after the Seven Kingdoms are united by the Targaryen Conquest, nearly 200 years before the events of Game of Thrones, and 172 years before the birth of Daenerys Targaryen. Featuring an ensemble cast, the show portrays the events leading up to the beginning of the decline of House Targaryen, a devastating war of succession known as the "Dance of the Dragons".

House of the Dragon received a straight-to-series order in October 2019, with casting beginning in July 2020 and principal photography starting in April 2021 in the United Kingdom. The series premiered on August 21, 2022, with the first season consisting of ten episodes. Five days after its premiere, the series was renewed for a second season. Sapochnik departed as showrunner after the first season, leaving Condal to serve as the sole showrunner for the second season.

The first season received highly positive reviews, with praise towards its character development, visual effects, writing, score by Ramin Djawadi and performances (particularly Considine, Smith, D'Arcy, Alcock, and Cooke). However, the pacing, specifically of the time jumps, and the dark lighting of some scenes were criticized. The series premiere was watched by over 10 million viewers across the linear channels and HBO Max on the first day, the biggest in HBO's history. In January 2023, the series won the Golden Globe Award for Best Television Series – Drama.
Question: Identify which instrument is string or percussion: Padayani thappu, Qanun
Answer: Qanun is string, Padayani thappu is percussion.
Question: Why does not the approach from English work on other languages?
Evidence: To date, the NLP community has focused primarily on approaches for detecting and mitigating gender stereotypes in English BIBREF5 , BIBREF6 , BIBREF7 . Yet, gender stereotypes also exist in other languages because they are a function of society, not of grammar. Moreover, because English does not mark grammatical gender, approaches developed for English are not transferable to morphologically rich languages that exhibit gender agreement BIBREF8 . In these languages, the words in a sentence are marked with morphological endings that reflect the grammatical gender of the surrounding nouns. This means that if the gender of one word changes, the others have to be updated to match. As a result, simple heuristics, such as augmenting a corpus with additional sentences in which he and she have been swapped BIBREF9 , will yield ungrammatical sentences. Consider the Spanish phrase el ingeniero experto (the skilled engineer). Replacing ingeniero with ingeniera is insufficient—el must also be replaced with la and experto with experta.
Moreover, because English does not mark grammatical gender, approaches developed for English are not transferable to morphologically rich languages that exhibit gender agreement BIBREF8 .
Answer: Because, unlike other languages, English does not mark grammatical genders
Question: How to be a human?
Answer: You have to have feelings and care about your fellow humans
Question: What are five different names I could pick for my new male dog?
Answer: Buddy, Rex, Fifo, Spot and Lucky
Question: What are some uses of Styrofoam?
Evidence: Styrofoam has a variety of uses. Styrofoam is composed of 98% air, making it lightweight and buoyant.

DuPont produces Styrofoam building materials, including varieties of building insulation sheathing and pipe insulation. The claimed R-value of Styrofoam insulation is five per inch.

Styrofoam can be used under roads and other structures to prevent soil disturbances due to freezing and thawing.

DuPont also produces Styrofoam blocks and other shapes for use by florists and in craft products. DuPont insulation Styrofoam has a distinctive blue color; Styrofoam for craft applications is available in white and green.
Answer: Styrofoam is used in building insulation, as a soil stabilization material,  and as crafting material.
Question: Extract all the names of people in this paragraph on the twelves apostles of Jesus, in a bullet point list.
Evidence: The three Synoptic Gospels record the circumstances in which some of the disciples were recruited, Matthew only describing the recruitment of Simon, Andrew, James, and John.

Despite Jesus only briefly requesting that they join him, they are all described as immediately consenting and abandoning their nets to do so. The immediacy of their consent has been viewed as an example of divine power, although this is not stated in the text. Another explanation is that some of the disciples may have heard of Jesus beforehand, as implied by the Gospel of John, which states that Andrew was a disciple of John the Baptist, and that he and his brother started following Jesus as soon as Jesus had been baptized.

Matthew describes Jesus meeting James and John, also fishermen and brothers, very shortly after recruiting Simon and Andrew. Matthew and Mark identify James and John as sons of Zebedee. Luke adds to Matthew and Mark that James and John worked as a team with Simon and Andrew. Matthew states that at the time of the encounter, James and John were repairing their nets, but readily joined Jesus without hesitation.

This parallels the accounts of Mark and Luke, but Matthew implies that the men have also abandoned their father (since he is present in the boat they abandon behind them), and Carter feels this should be interpreted to mean that Matthew's view of Jesus is one of a figure rejecting the traditional patriarchal structure of society, where the father had command over his children; most scholars, however, just interpret it to mean that Matthew intended these two to be seen as even more devoted than the other pair, or that Jesus expected the imminent coming of the kingdom.

The Synoptic Gospels go on to describe that later in Jesus' ministry he noticed a tax collector in his booth. The tax collector, called Matthew in Matthew 9:9, and Levi in Mark 2:14 and Luke 5:27, is asked by Jesus to become one of his disciples. Matthew/Levi is stated to have accepted and then invited Jesus for a meal with his friends. Tax collectors were seen as villains in Jewish society, and the Pharisees are described as asking Jesus why he is having a meal with such disreputable people. The reply Jesus gave is now well known: "it is not the healthy who need a doctor, but the sick. I have not come to call the righteous, but sinners to repentance."
Answer: - Matthew
- Simon
- Andrew
- James
- John
- Jesus
- John the Baptist
- Mark
- Zebedee
- Luke
- Carter
- Levi
Question: Write a diary entry for a dog that only likes one person that lives in the house on a day that their favorite person was gone all day.
Answer: Today was a challenging day, after the quiet time, my two legged housemates started making noise at the normal time, changing their appearances and eating food that I was not allowed to eat. The smaller ones left with the other one as usual, but then I saw the best one disappeared as well through the door with the comfortably cold floor. I check the floor in the food room for crumbs, take a drink and then wait for forever for the sound of the best one to return. Small, mouth-sized intruders visited the outside throughout the day, and I let them know they are not welcome. I fear the worst, and the small ones and the other one returned, but the best one is missing. They bribe me with food and water, distracting me from noticing the best one has not returned. I stay on the cold floor, the last place I saw the best one while the others do their best to distract me. I will not be fooled. I hear the rumbling sound that means the best one returns. I'm the first to greet them, because I love them best. I am reminded that I am the best, and I keep the best one in my sight until everything is quiet once again.
Question: Why was Abraham Lincoln a great President?
Answer: Abraham Lincoln's strengths were his empathy and unquenchable thirst to always be learning.  He grew up in a humble beginnings where his passions involved reading.  He become a self-taught lawyer.  During the Civil War, he dove into books of military history.  After two years of war, he learned to trust his instincts and installed the right general leadership to execute and win the war.  He was the near perfect example of an orator.  Not long winded but delivered his powerful rhetoric in the just right amount.
Question: I'm considering buying a bicycle. How do I know which one I should buy?
Answer: It depends on how you want to use the bike and how much budget you have. If you just need one for commute, consider an electric bike if you want to go for a long distance with little effort, or a folding bike if you need to carry it with your car or onto public transportation. Or if you want to buy one for sports, consider a road bike for road cycling, or a mountain bike for tail cycling. A sport bike's price can range from $100s to $1000s. Higher-end bikes usually comes with better material like carbon-fiber or Titanium alloy, which are light-weighted and at the same time sturdy. There are also different types of gear switch and breaks, that can affect the price. Finally, bikes come with different sizes of frame and wheels, you need to find one that fits your body height. Go to a local bike shop and talk to a sales agent to find a bike that best fit your need.
Question: What is a time signature in music?
Answer: The time signature in music represents the number of notes in each bar. The time signature is noted at the start of a composition as is represented as two stacked numbers. For example the common time signature 4/4 indicates each bar will contain four quarter note beats.
Question: From the passage identify the sacred animals of Apollo. Display the results in a comma separated format.
Evidence: Apollo (Ἀπόλλων, Apóllōn)

God of music, arts, knowledge, healing, plague, prophecy, poetry, manly beauty, and archery. He is the son of Zeus and Leto, and the twin brother of Artemis. Both Apollo and Artemis use a bow and arrow. Apollo is depicted as young, beardless, handsome and athletic. In myth, he can be cruel and destructive, and his love affairs are rarely happy. He is often accompanied by the Muses. His most famous temple is in Delphi, where he established his oracular shrine. His signs and symbols include the laurel wreath, bow and arrow, and lyre. His sacred animals include roe deer, swans, and pythons. Some late Roman and Greek poetry and mythography identifies him as a sun-god, equivalent to Roman Sol and Greek Helios.
Answer: roe deer, swans, pythons
Question: Identify which animal species is alive or extinct: Wiwaxia, Penguin
Answer: Penguin is alive, Wiwaxia is extinct.
Question: What network do the authors use in this paper?
Evidence: We participated in the WMT 2016 shared news translation task by building neural translation systems for four language pairs: English INLINEFORM0 Czech, English INLINEFORM1 German, English INLINEFORM2 Romanian and English INLINEFORM3 Russian. Our systems are based on an attentional encoder-decoder BIBREF0 , using BPE subword segmentation for open-vocabulary translation with a fixed vocabulary BIBREF1 . We experimented with using automatic back-translations of the monolingual News corpus as additional training data BIBREF2 , pervasive dropout BIBREF3 , and target-bidirectional models.
Our systems are based on an attentional encoder-decoder, using BPE subword segmentation for open-vocabulary translation with a fixed vocabulary.
Answer: An attentional encoder-decoder network.
Question: Why is crypto currency risky?
Answer: Cryptocurrency is risk for a number of reasons.  The price fluctuations are usually driven by large institutional investors not individuals.  When institutions pull out their money you can see price fluctuations as high as 90% loss.  It is a deregulated digital currency with no government oversight so if your money gets hacked or taken because a bad actor got your wallet keys your money is lost for good, you will never get it back, and there will never be an investigation into where your money went.  If you are going to play in the crypto currency space its best to use a platform similar to coinbase that has security measures in place for all your crypto wallets so your money doesn't get stolen.