DataHammer/scimrc huggingface dataset:
Question: Why the SQUAD's average candidates per question (c/q) is the smallest?
Evidence: All corpora provide datasets/splits for answer selection, whereas only (WikiQA, SQuAD) and (WikiQA, SelQA) provide datasets for answer extraction and answer triggering, respectively. SQuAD is much larger in size although questions in this corpus are often paraphrased multiple times. On the contrary, SQuAD's average candidates per question ( INLINEFORM0 ) is the smallest because SQuAD extracts answer candidates from paragraphs whereas the others extract them from sections or infoboxes that consist of bigger contexts. Although InfoboxQA is larger than WikiQA or SelQA, the number of token types ( INLINEFORM1 ) in InfoboxQA is smaller than those two, due to the repetitive nature of infoboxes.
All corpora show similar average answer candidate lengths ( INLINEFORM0 ), except for InfoboxQA where each line in the infobox is considered a candidate. SelQA and SQuAD show similar average question lengths ( INLINEFORM1 ) because of the similarity between their annotation schemes. It is not surprising that WikiQA's average question length is the smallest, considering their questions are taken from search queries. InfoboxQA's average question length is relatively small, due to the restricted information that can be asked from the infoboxes. InfoboxQA and WikiQA show the least question-answer word overlaps over questions and answers ( INLINEFORM2 and INLINEFORM3 in Table TABREF2 ), respectively. In terms of the F1-score for overlapping words ( INLINEFORM4 ), SQuAD gives the least portion of overlaps between question-answer pairs although WikiQA comes very close.
Fig. FIGREF4 shows the distributions of seven question types grouped deterministically from the lexicons. Although these corpora have been independently developed, a general trend is found, where the what question type dominates, followed by how and who, followed by when and where, and so on.
Fig. FIGREF6 shows the distributions of answer categories automatically classified by our Convolutional Neural Network model trained on the data distributed by li:02a. Interestingly, each corpus focuses on different categories, Numeric for WikiQA and SelQA, Entity for SQuAD, and Person for InfoboxQA, which gives enough diversities for statistical learning to build robust models.
On the contrary, SQUAD’s average candidates per question (c/q) is the smallest because SQUAD extracts answer candidates from paragraphs whereas the others extract them from sections or infoboxes that consist of bigger contexts.
Answer: Because SQUAD extracts answer candidates from paragraphs whereas the others extract them from sections or infoboxes that consist of bigger contexts.
Question: What are some common designs in flash tattoos?
Answer: Common designs in flash tattoos include skulls, knives, mermaids, panthers, sparrows, hearts, eagles, anchors, flowers, roses, butterflies, hands, snakes, and faces.
Question: Was Furze Hill an established community in the 19th century?
Evidence: Furze Hill (or Furzehill) is a hamlet situated in the New Forest National Park of Hampshire, England. It is in the civil parish of Ellingham, Harbridge and Ibsley. Its nearest town is Fordingbridge, which lies approximately 3.1 miles (5.2 km) north-west from the hamlet.

Furze Hill is a hamlet in the civil parish of Hyde. It is situated on low ground on either side of Huckles Brook on the South Gorley to Ogdens road. The houses are surrounded by fields and paddocks. Additional houses can be found at the southern edge of Gorley Common lining a narrow track to North Gorley.

Furze Hill is the most recent settlement in the parish of Hyde, becoming an established community only in the 20th century.
Answer: No, it was not an established community until the 20th century.
Question: Are synonymous relation taken into account in the Japanese-Vietnamese task?
Evidence: Due to the fact that Vietnamese WordNet is not available, we only exploit WordNet to tackle unknown words of Japanese texts in our Japanese$\rightarrow $Vietnamese translation system. After using Kytea, Japanese texts are applied LSW algorithm to replace OOV words by their synonyms. We choose 1-best synonym for each OOV word. Table TABREF18 shows the number of OOV words replaced by their synonyms. The replaced texts are then BPEd and trained on the proposed architecture. The largest improvement is +0.92 between (1) and (3). We observed an improvement of +0.7 BLEU points between (3) and (5) without using data augmentation described in BIBREF21.
After using Kytea, Japanese texts are applied LSW algorithm to replace OOV words by their synonyms. 
Answer: Yes.
Question: Identify the bird from the list: Butter, Bittern, Bitterness
Answer: Bittern
Question: If I have a dollar, two nickels and a quarter, how much money in total do I have. Please respond with numbers and the dollar sign only, no words.
Answer: $1.35
Question: Why are some people in Argentina called Portenos?
Answer: "Porteños" comes from the word Puerto, which means Port in Spanish. Porteños was first introduced to describe the people that lived near the main Port in Argentina which is in Buenos Aires, the Capital of Argentina. So Porteños is used to refer to people that live in Buenos Aires. If referring to a female the right use of the word would be PorteñA, with an "a" at the end.
Question: Tell me which one does not fit with the group:  Blue, Green, White, Yellow
Answer: All except White are colors of the rainbow.
Question: In what part of the United States is the New England region?
Answer: New England is located in the northeast of the United States.
Question: What does Frege's holistic and functional approach to meaning states?
Evidence: Frege promoted what we could call sentence holism: “Only in the context of a sentence does a word have a meaning.” BIBREF10 We will later use its modern reformulation to show an analogy with certain neural language models and therefore their holistic character.
Frege promoted what we could call sentence holism: “Only in the context of a sentence does a word have a meaning.” BIBREF10
Answer: The answers are shown as follows:
* Only in the context of a sentence does a word have a meaning.
Question: Is there any human evaluation involved in evaluating this famework?
Evidence: Due to the lack of available models for the task, we compare our framework with a previous model developed for image-to-image translation as baseline, which colorizes images without text descriptions. We carried out two human evaluations using Mechanical Turk to compare the performance of our model and the baseline. For each experiment, we randomly sampled 1,000 images from the test set and then turned these images into black and white. For each image, we generated a pair of two images using our model and the baseline, respectively. Our model took into account the caption in generation while the baseline did not. Then we randomly permuted the 2,000 generated images. In the first experiment, we presented to human annotators the 2,000 images, together with their original captions, and asked humans to rate the consistency between the generated images and the captions in a scale of 0 and 1, with 0 indicating no consistency and 1 indicating consistency. In the second experiment, we presented to human annotators the same 2,000 images without captions, but asked human annotators to rate the quality of each image without providing its original caption. The quality was rated in a scale of 0 and 1, with 0 indicating low quality and 1 indicating high quality.
We carried out two human evaluations using Mechanical Turk to compare the performance of our model and the baseline.
Answer: Yes.
Question: Where was Sarah Schechter born?
Evidence: Schechter was born in Boston and grew up in Brookline, Massachusetts and New York City. Her father, Danny Schechter, a grandson of Russian-Jewish immigrant socialists, was a human rights activist, author, filmmaker and television producer.
Answer: Sarah Schechter was born in Boston, Massachusetts.
Question: What is a, "one-timer" in ice hockey?
Answer: Ice hockey is a sport typically played with one goalie and five skaters on each of two opposing teams.  A one-timer is an expression used to describe a shot taken by a player directly from a pass of another player in a single motion.  This does not necessarily have to be a shot on goal, but a one-timer is so named to describe the backswing and striking of the puck from a pass, deflection or re-direction without stopping or accepting the puck first.  The idea behind the name one-timer refers to the idea the shooter has one opportunity to make contact with the puck in this manner and without proper time is at risk of missing the shot entirely due to the puck being in motion as the shot is attempted.
Question: What is supply and demand?
Answer: Supply and demand are economic terms in a free-market economy that dictate the price of a good or service. Typically shown on a two-dimensional axis where y is price and x is the quantity, the price of a particular good or service is when the two linear lines intersect. Supply has a negative sloping line indicating that when demand is fixed an increase in quantity of a good or service results in a lower unit price of that good or service. Demand has a positive linear line meaning that has more demand for a good or item increases while supply remains fixed then the price for that good or service increases.
Question: What is the baseline of this paper?
Evidence: The Humor Analysis based on Human Annotation (HAHA) 2019 BIBREF1 competition asked for analysis of two tasks in the Spanish language based on a corpus of publicly collected data described in Castro et al. BIBREF2 :
The HAHA dataset includes labeled data for 24,000 tweets and a test set of 6,000 tweets (80%/20% train/test split.) Each record includes the raw tweet text (including accents and emoticons), a binary humor label, the number of votes for each of five star ratings and a “Funniness Score” that is the average of the 1 to 5 star votes cast. Examples and data can be found on the CodaLab competition webpage.
Task and Dataset Description The Humor Analysis based on Human Annotation (HAHA) 2019 competition asked for analysis of two tasks in the Spanish language based on a corpus of publicly collected data described in Castro et al.
Answer: A corpus of publicly collected data described in Castro et al.
Question: Which President of the US was less of a hawk than people supposed?
Answer: Ronald Regan. Although he was considered an arch conservative and ardent neoliberal, he took a liberal approach to arms control. It was Regan who drove for a reduction in strategic arms with Mikhail Gorbachev on a walk by Lake Geneva when he asked if the US was attacked by Aliens "would you help us?". Gorbachev replied "No doubt about it" and they two found a starting point to a long arms reduction discussion between the two powers and Regan took the initiative to make an offer of deep cuts in arms levels in Reykjavik less than a year later.
Question: What is the best way to cook a steak?
Answer: There are many different variants to cooking a steak. You must choose the proper temperature to cook a steak. The range is from rare, medium rare, medium, medium well to well done. There are several ways to cook a steak for example a grill or in a pan. For this example we will use a grill. Remove steak from fridge and season. Allow steak to warm to near room temperature. This will prevent a steak from drying out and improve taste. Cook the steak to the desired temperature trying to only flip 1-3 times. Once done allow meat to rest for 5 minutes for best flavor.
Question: Given this paragraph about Twitch, during what year did twitch have more than 100 million viewers per month?
Evidence: Twitch is an American video live streaming service that focuses on video game live streaming, including broadcasts of esports competitions, in addition to offering music broadcasts, creative content, and "in real life" streams. Twitch is operated by Twitch Interactive, a subsidiary of Amazon.com, Inc. It was introduced in June 2011 as a spin-off of the general-interest streaming platform Justin.tv. Content on the site can be viewed either live or via video on demand. The games shown on Twitch's current homepage are listed according to audience preference and include genres such as real-time strategy games (RTS), fighting games, racing games, and first-person shooters.

The popularity of Twitch eclipsed that of its general-interest counterpart. In October 2013, the website had 45 million unique viewers, and by February 2014, it was considered the fourth-largest source of peak Internet traffic in the United States. At the same time, Justin.tv's parent company was re-branded as Twitch Interactive to represent the shift in focus – Justin.tv was shut down in August 2014. That month, the service was acquired by Amazon for US$970 million, which later led to the introduction of synergies with the company's subscription service Amazon Prime. Twitch acquired Curse LLC in 2016, an operator of online video gaming communities and introduced means to purchase games through links on streams along with a program allowing streamers to receive commissions on the sales of games that they play.

By 2015, Twitch had more than 100 million viewers per month. In 2017, Twitch remained the leading live streaming video service for video games in the US, and had an advantage over YouTube Gaming, which shut down its standalone app in May 2019. As of February 2020, it had 3 million broadcasters monthly and 15 million daily active users, with 1.4 million average concurrent users. As of May 2018, Twitch had over 27,000 partner channels.
Answer: Twitch surpassed 100 million viewers per month in the year 2015.
Question: What countries make up the Benelux region?
Answer: The Benelux region is compromised of the following countries: Belgium, the Netherlands and Luxembourg.
Question: Why should you live in Florida?
Answer: Florida is a great place to live if you like the sun, warm days, spending time at the beach and enjoying a relaxing lifestyle. There are many things to do in Florida such as visiting Disney World, Universal Studios, The Kennedy Space Center or the many aquariums through the state.  There are several amazing beaches throughout the state but one of my favorites is Siesta Key because of it's powder white sand that doesn't get hot.  You do have to keep an eye out for Sting Rays but beyond that the gulf is great to swim in.  There are things to do all day on Siesta key from the beach to the village with multiple restaurants and shops.  The only requirement is to relax and enjoy the time you have in a laid back tropical atmosphere.
Question: Why do they utilize Portable textual information?
Evidence: In recent studies, deep learning models have achieved top performances in emotion detection and classification. Access to large amount of data has contributed to these high results. Numerous efforts have been dedicated to build emotion classification models, and successful results have been reported. In this work, we combine several popular emotional data sets in different genres, plus the one given for this task to train the emotion model we developed. We introduce a multigenre training mechanism, our intuition to combine different genres are a) to augment more training data, b) to generalize detection of emotion. We utilize Portable textual information such as subjectivity, sentiment, and presence of emotion words, because emotional sentences are subjective and affectual states like sentiment are strong indicator for presence of emotion.
The rest of this paper is structured as followings: section SECREF2 introduce our neural net model, in section SECREF3 we explain the experimental setup and data that is been used for training and development sets, section SECREF4 discuss the results and analyze the errors, section SECREF5 describe related works, section SECREF6 conclude our study and discuss future direction.
We utilize Portable textual information such as subjectivity, sentiment, and presence of emotion words, because emotional sentences are subjective and affectual states like sentiment are strong indicator for presence of emotion.
Answer: Because emotional sentences are subjective and affectual states like sentiment are strong indicator for presence of emotion.
Question: Give me tips on how to stick to habits?
Answer: It is sometimes tough to stick to habits, but it is possible if we follow the methodic approach.

Here are some tips on how you can do it.

1. Understand why you need to stick to a habit and why it is essential.
2. Make the habit obvious; e.g., if you want to play guitar every night after dinner, keep your guitar visible in the dining area.
3. Make habits easy. We often avoid long and complex things, so keep them simple. e.g., if you want to make a habit of exercising, start with small and simple exercises.
4. Make habits attractive and satisfying. Give yourself rewards after finishing the routine. e.g., you can eat an ice cream cone after exercise 3–4 days a week.

I hope this helps you in your habit-making journey.
Question: What does the author prove with this paper?
Evidence: In this paper, we showed that by jointly learning the tasks of ternary and fine-grained classification with a multitask learning model, one can greatly improve the performance on the second. This opens several avenues for future research. Since sentiment is expressed in different textual types like tweets and paragraph-sized reviews, in different languages (English, German, ..) and in different granularity levels (binary, ternary,..) one can imagine multitask approaches that could benefit from combining such resources. Also, while we opted for biLSTM networks here, one could use convolutional neural networks or even try to combine different types of networks and tasks to investigate the performance effect of multitask learning. Lastly, while our approach mainly relied on the foundations of BIBREF4 , the internal mechanisms and the theoretical guarantees of multitask learning remain to be better understood.
In this paper, we showed that by jointly learning the tasks of ternary and fine-grained classification with a multitask learning model, one can greatly improve the performance on the second.
Answer: They showed that by jointly learning the tasks of ternary and fine-grained classification with a multitask learning model, one can greatly improve the performance on the second.
Question: Pulitzer Prize 2022 was given to  4 Indian photographers from Reuters news agency. Name them
Answer: Danish Siddiqui(slain), Adnan Abidi, SannaIrshad Matto & Amit Dave
Question: What are some must visit places in San Diego, CA?
Answer: San Diego is known as a sunny state and is one of those places in the US that receives most sun light through out the year. People from all over the US visit San Diego. Here are some must visit places in San Diego:
- San Diego Zoo
- Balboa Park
- USS Midway Museum
- Safari Park
- Seaworld San Diego
- Belmont Park
Question: Which of these are not playable races on Dungeons and Dragons 5th edition: Giant, Gnome, Half-Elf, Chimera, Kenku, Troll, Gnoll
Answer: From this list, Giant, Chimera, Troll and Gnoll are not playable races in Dungeons and Dragons 5th edition, although there is a race similar to the concept of giants called Firbolg.
Question: What metrics are used for evaluation?
Evidence: The Density Ratio method consistently outperformed Shallow Fusion for the cross-domain scenarios examined, with and without fine-tuning to audio data from the target domain. Furthermore, the gains in WER over the baseline are significantly larger for the Density Ratio method than for Shallow Fusion, with up to 28% relative reduction in WER (17.5% $\rightarrow $ 12.5%) compared to up to 17% relative reduction (17.5% $\rightarrow $ 14.5%) for Shallow Fusion, in the no fine-tuning scenario.
Furthermore, the gains in WER over the baseline are significantly larger for the Density Ratio method than for Shallow Fusion, with up to 28% relative reduction in WER (17.5% $\rightarrow $ 12.5%) compared to up to 17% relative reduction (17.5% $\rightarrow $ 14.5%) for Shallow Fusion, in the no fine-tuning scenario.
Answer: word error rate
Question: Write a witty paragraph about a chicken's thought process for crossing the road.
Answer: Oh my, that is a lovely shrub over there past the black track. I wonder if it smells as good as I imagine it would. I do wonder if all the fast folks passing by know this shrub and thus are not bothered by the curiosity. There is no way around it; I have to get close to confirm it.
Question: Extract the celebrity guests that appeared on the show Parks and Recreation.
Evidence: Numerous actors have made recurring guest appearances throughout the series, including Pamela Reed as Leslie's mother and fellow politician Marlene Griggs-Knope, Ben Schwartz as Tom's fast-talking friend Jean-Ralphio and Jenny Slate as his twin sister Mona-Lisa, Jama Williamson as Tom's ex-wife Wendy, Mo Collins as morning talk show host Joan Callamezzo, Jay Jackson as television broadcaster Perd Hapley, Alison Becker as newspaper reporter Shauna Malwae-Tweep, Darlene Hunt as conservative activist Marcia Langman, and Andy Forrest as Andy's frequent shoeshine customer Kyle. Megan Mullally, the real-life wife of Nick Offerman, portrayed Ron's ex-wife Tammy in the second season's "Ron and Tammy", a role she reprised in later episodes. Lucy Lawless and Jon Glaser have recurring roles in the fifth and sixth seasons as Ron's love interest and later wife Diane Lewis, and as Leslie's arch enemy on the city council Jeremy Jamm, respectively.

Mullally's performance was well received, which made the Parks and Recreation producers feel more comfortable about using celebrity guest actors in later episodes. Other such celebrity guests included: Blake Anderson, Fred Armisen, Will Arnett, Kristen Bell, H. Jon Benjamin, Matt Besser, Chris Bosh, Louis C.K., The Decemberists, Sam Elliott, Will Forte, Ginuwine, Michael Gross, Jon Hamm, Nick Kroll, John Larroquette, Andrew Luck, Letters to Cleo, Natalie Morales, Parker Posey, Kathryn Hahn, Andy Samberg, J. K. Simmons, Roy Hibbert, Detlef Schrempf, Justin Theroux, Wilco, Henry Winkler, Peter Serafinowicz and Yo La Tengo. Paul Rudd appeared in several season four episodes as Bobby Newport, Leslie's opponent in the City Council race, and returned for two episodes in the final season.
Answer: Pamela Reed, Ben Schwartz, Jenny Slate, Jama Williamson, Mo Collins, Jay Jackson, Alison Becker, Darlene Hunt, Andy Forrest, Megan Mullally, Lucy Lawless, Jon Glaser, Blake Anderson, Fred Armisen, Will Arnett, Kristen Bell, H. Jon Benjamin, Matt Besser, Chris Bosh, Louis C.K., The Decemberists, Sam Elliott, Will Forte, Ginuwine, Michael Gross, Jon Hamm, Nick Kroll, John Larroquette, Andrew Luck, Letters to Cleo,Natalie Morales, Parker Posey,
 Kathryn Hahn, Andy Samberg, J. K. Simmons, Roy Hibbert, Detlef Schrempf, Justin Theroux, Wilco, Henry Winkler, Peter Serafinowicz, Yo La Tengo, Paul Rudd