DataHammer/scimrc huggingface dataset:
Question: From the following passage, extract the device used to shoot this film.
Evidence: High Flying Bird is a 2019 American sports drama film directed by Steven Soderbergh, from a story suggested by André Holland, with the screenplay by Tarell Alvin McCraney. The film stars Holland, Zazie Beetz, Melvin Gregg, Sonja Sohn, Zachary Quinto, Glenn Fleshler, Jeryl Prescott, Justin Hurtt-Dunkley, Caleb McLaughlin, Bobbi Bordley, Kyle MacLachlan and Bill Duke, with additional appearances of basketball players Reggie Jackson, Karl-Anthony Towns and Donovan Mitchell. The film follows a sports agent who must pull off a plan in 72 hours, pitching a controversial opportunity to his client, a rookie basketball player during the company’s lockout. The film was shot entirely on the iPhone 8, becoming Soderbergh's second film to be shot on an iPhone, after Unsane.
Answer: High Flying Bird is a 2019 American sports drama film that was shot on the iPhone 8.
Question: Give me a list of the best adventure books
Answer: Here's a list of popular adventure books: 
- Into the wild, Jon Krakauer 
- Into thin air, Jon Krakauer 
- Arctic Dreams, Barry Lopez
- Horizon, Barry Lopez 
- On Trails, Robert Moor
- Moby Dick, Herman Melville 
- Treasure Island - RL Stevenson 
- White Fang - Jack London 
- Life of Pi - Yann Martel
- The Hobbit - J.R.R Tolkien 
- Jurassic Park - Michael Crichton
Question: Which languages do they test on?
Evidence: Space requirements might still be considerable (comparable to those used by n-gram language models), and similar tricks can be used to reduce memory usage BIBREF27 . The above pseudocode is agnostic with respect to the choice of fragmentation and environment functions; task-specific choices are described in more detail for each experiment below.
Discussion
The above pseudocode is agnostic with respect to the choice of fragmentation and environment functions; task-specific choices are described in more detail for each experiment below.

Discussion
Answer: Answer with content missing: (Applications section) We use Wikipedia articles
in five languages
(Kinyarwanda, Lao, Pashto, Tok Pisin, and a subset of English) as well as the Na dataset of Adams
et al. (2017).
Select:
Kinyarwanda, Lao, Pashto, Tok Pisin, and a subset of English
Question: What is the best tea  near Bangalore
Answer: Munnar and Kunnar is the best tea produced near Bangalore
Question: The founder of Gupta dynasty was
Answer: The founder of the Gupta dynasty was Chandragupta Maurya.
Question: What three datasets are used to measure performance?
Evidence: In this study, we evaluate our model on three real KG including two typical large-scale knowledge graph: Freebase BIBREF0, DBpedia BIBREF1 and a self-construction game knowledge graph. First, we adapt a dataset extracted from Freebase, i.e., FB24K, which used by BIBREF26. Then, we collect extra entities and relations that from DBpedia which that they should have at least 100 mentions BIBREF7 and they could link to the entities in the FB24K by the sameAs triples. Finally, we build a datasets named as DBP24K. In addition, we build a game datasets from our game knowledge graph, named as Game30K. The statistics of datasets are listed in Table TABREF24.
In this study, we evaluate our model on three real KG including two typical large-scale knowledge graph: Freebase BIBREF0, DBpedia BIBREF1 and a self-construction game knowledge graph. First, we adapt a dataset extracted from Freebase, i.e., FB24K, which used by BIBREF26. Then, we collect extra entities and relations that from DBpedia which that they should have at least 100 mentions BIBREF7 and they could link to the entities in the FB24K by the sameAs triples. Finally, we build a datasets named as DBP24K. In addition, we build a game datasets from our game knowledge graph, named as Game30K. The statistics of datasets are listed in Table TABREF24.
Answer: The answers are shown as follows:
* Freebase BIBREF0, DBpedia BIBREF1 and a self-construction game knowledge graph
Question: How do you do a shuffle ball change tap move?
Answer: First, shuffle with your right foot, step back with on to the ball of your right foot.  Next, stomp with your whole left foot.  Repeat.
Question: Why did naatu naatu get oscar for best original song?
Answer: Naatu Naatu became a global sensation and quickly went viral on social media after the film's release ast year. The songs quick tempo and synchronized choreography were an instant hit with the audiences. The song was composed by MM Keeravani with lyrics written by Chandrabose. Naatu Naatu already made history once in January when it won the Golden Globe for best original song, defeating contenders like Rihanna, Taylor Swift and Lady Gaga. The same month, the song also won the Critics Choice award for the best song. It did not get the award just for the music, the song captures the essence of the full movie and has other elements such as nice dance, nice setting, nice location and nice production.
Question: Who founded the Society of Jesus, and what are they more commonly known as?
Evidence: The Society of Jesus, commonly known as the Jesuits, is a religious order of clerics regular of pontifical right for men in the Catholic Church headquartered in Rome. It was founded in 1540 by Ignatius of Loyola and six companions, with the approval of Pope Paul III. The society is engaged in evangelization and apostolic ministry in 112 nations. Jesuits work in education, research, and cultural pursuits. Jesuits also conduct retreats, minister in hospitals and parishes, sponsor direct social and humanitarian ministries, and promote ecumenical dialogue.
Answer: The Society of Jesus are more commonly known as the Jesuits and were founded in 1540 by Ignatius of Loyola and six of his companions.  They are known for their work in the field of education.
Question: What species of fish are found in the Pamlico Sound?
Answer: The Pamlico Sound has three primary species of fish: Red Drum, Southern Flounder and Spotted Seatrout.  Depending on the time of year, different species will be more prevalent.  Visit the North Carolina Wildlife Resource Commission website to learn more.
Question: Is Apple better than Samsung?
Answer: Each brands have their own pros and cons. It is the matter of preference whether or not someone likes a specific brand. You should decide on your own what is or isn't important for you in a brand and pick accordingly.
Question: How big is ICSI meeting corpus?
Evidence: The ICSI Meeting Corpus BIBREF11 is a collection of meeting recordings that has been thoroughly annotated, including annotations for involvement hot spots BIBREF12, linguistic utterance units, and word time boundaries based on forced alignment. The dataset is comprised of 75 meetings and about 70 hours of real-time audio duration, with 6 speakers per meeting on average. Most of the participants are well-acquainted and friendly with each other. Hot spots were originally annotated with 8 levels and degrees, ranging from `not hot' to `luke warm' to `hot +'. Every utterance was labeled with one of these discrete labels by a single annotator. Hightened involvement is rare, being marked on only 1% of utterances.
The ICSI Meeting Corpus BIBREF11 is a collection of meeting recordings that has been thoroughly annotated, including annotations for involvement hot spots BIBREF12, linguistic utterance units, and word time boundaries based on forced alignment. The dataset is comprised of 75 meetings and about 70 hours of real-time audio duration, with 6 speakers per meeting on average. Most of the participants are well-acquainted and friendly with each other. Hot spots were originally annotated with 8 levels and degrees, ranging from `not hot' to `luke warm' to `hot +'. Every utterance was labeled with one of these discrete labels by a single annotator. Hightened involvement is rare, being marked on only 1% of utterances.
Answer: The answers are shown as follows:
*  75 meetings and about 70 hours of real-time audio duration
Question: Classify each of the following as "Motorized" or "Not Motorized": Bicycle, Skateboard, Car, Lawn Mower, Tractor, Golf Cart
Answer: Bicycle: Not Motorized
Skateboard: Not Motorized
Car: Motorized
Lawn Mower: Motorized
Tractor: Motorized
Golf Cart: Motorized
Question: How much data do the authors gather?
Evidence: In the process, we have gather a total of 449 expert judgments (one expert failed to answer a given problem), 146 missing hypotheses and 47 explanations for negative judgments.
Despite being marked as “yes”, the problems with a reported missing hypothesis should really be classified as “no”, if one does not assume external knowledge. (See below for further discussion on the reported missing hypotheses.) Thus crunching the numbers, we see that more that half of the responses express some doubt about entailment. Remember that all problems were marked as “yes” by the creators of the RTE3 testsuite — we find here that one average, one expert in two is likely to cast a doubt over this “yes”.
However, each problem was classified by three experts. The histogram below shows the distribution of number of experts casting doubt on entailment, over all problems.
[ybar interval, ymax=0.5,ymin=0, minor y tick num = 0] coordinates (0, 0.26666666666666666) (1, 0.17333333333333334) (2, 0.3466666666666667) (3, 0.21333333333333335) (4,0) ;
Unfortunately we can only draw preliminary conclusions, due to the limited number of respondents for each problem. However, we can make the following observations:
We find this level of agreement indicative of a good level of reliability. Additionally, with three experts per problem, we are very likely to discover most missing hypotheses and incorrect entailments.
In our compilation of answers, we have marked 42 problems as straight “No”, 64 as “Yes” with missing implicit hypotheses and “44” as plain “Yes”. This means that, we expect, in our opinion, 28% of problems to be incorrectly labeled in RTE3 even assuming reasonable world knowledge. An additional 42% of problems require additional (yet reasonable to assume) hypotheses for entailment to hold formally, as prescribed by RTE3. This leaves only 30% of problems to acceptable as such. The reason that the amount of doubt is larger than in the average numbers quoted above is that, for many problems, certain missing hypotheses and/or error were not detected by a majority experts, but, after careful inspection, we judge that the minority report is justified.
We have additionally tagged each missing hypothesis according to the following classification:
In the process, we have gather a total of 449 expert judgments (one expert failed to answer a given problem), 146 missing hypotheses and 47 explanations for negative judgments.
Answer: They have gather a total of 449 expert judgments (one expert failed to answer a given problem), 146 missing hypotheses and 47 explanations for negative judgments.
Question: How does the Harvard housing system work?
Answer: First-Year students live in one of the seventeen dormitories located in and around Harvard Yard. Rooms are assigned based on a brief survey sent to admitted students. The survey asks questions like “How many roommates do you want?”, “How comfortable are you with noise?”, and “What type of music do you listen to?”. After the first year, the majority of students move into one of the twelve residential Houses. Houses are assigned in March of a student’s first year. Rather than randomly assigning individual students to houses and scattering close friends, students can assemble into “blocking groups” of no greater than 8 students and each group is randomly assigned to a House. If 8 friends aren’t enough, two blocking groups can link themselves in the lottery. Linked groups will not be assigned the same House but are guaranteed to be assigned the same Neighborhood (e.g. The Quad).
Question: Explain the difference of position against the Western Bloc among the Soviet leaders cited in the text.
Evidence: From 1957 through 1961, Khrushchev openly and repeatedly threatened the West with nuclear annihilation. He claimed that Soviet missile capabilities were far superior to those of the United States, capable of wiping out any American or European city. According to John Lewis Gaddis, Khrushchev rejected Stalin's "belief in the inevitability of war," however. The new leader declared his ultimate goal was "peaceful coexistence". In Khrushchev's formulation, peace would allow capitalism to collapse on its own, as well as giving the Soviets time to boost their military capabilities, which remained for decades until Gorbachev's later "new thinking" envisioning peaceful coexistence as an end in itself rather than a form of class struggle.
Answer: Stalin believed that war against the Western Bloc was inevitable.
Krushchev instead believed the two blocs could avoid war because the war was not necessary to establish the Eastern Bloc's superiority; the Western Bloc would fail systemically.
On the other hand, Gorbachev truly believed in peaceful coexistence between the two blocs.
Question: What is data engineering?
Answer: Data engineering deals with building systems and process that bring data together and serve that data up to the business.  They ingest data, transform, data, apply data quality rules, and prepare finalized cleaned datasets for use by the business to get insights.  Data engineers have to be strong developers as well if data engineering has to be done using a programming language like Python.
Question: Tell a story with the following: A guy that lives in San Jose California, he is a data scientist, he is in his mid 40's and he is aspiring to build an LLM model that will change the world
Answer: John is a data scientist living in San Jose California. He is in his mid 40s and has always been passionate about data science. He has always dreamed of creating a model that would revolutionize the world, but he has been struggling to find the right approach.

One day, John stumbled across a book that discussed a new way of approaching data science. He read it and was amazed by the concepts presented in the book. He immediately started to apply the ideas in the book and soon realized that he had found his calling. He quickly put together an LLM model that was capable of solving some of the most difficult data science problems. 

John shared his model with the world and it quickly became a success. He was able to solve some of the most complex data science problems and he was able to prove that his model was better than any other model available. John was able to change the world and he is now considered one of the most successful data scientists in the world.
Question: Why would people not like Goose Goose Duck?
Answer: the core mechanism is built on the premise of acting/lying, which is not a prevalent skill in today’s population. Unlike Texas Hold’em, where a player only needs to lie to play well can also enjoy it without lying, GGD and WW require all players to have the capacity to lie. If one participant is a bad liar, the whole game is ruined. This is because in its essence, GGD is a game where a set of players guard a secret, and the rest of players uncover that secret. To make this process fun and intellectually stimulating, we first need to remove the more obvious secret-revealing signals like voice tones and facial expressions. What’s worse, it only takes 1 player to leak the secret for everyone, which imposes an incredibly high entry barrier
Question: What are some ideas for fun rainy day activities to do with a 7 year old?
Answer: * Play board games! Kids 6+ love to play board games of all kinds. You likely have a few sitting at home - dust them off and have at it!
* Learn Chess! You may be surprised, but chess comes naturally to most kids, and many of them love the idea of horses, castles, kings and queens all battling against each other. While chess can take years to master, it is easy and fun to get started.
* Go to the library! Libraries are great places to spend a rainy day, while giving you a chance to get out of the house. Many libraries have kids areas and besides books, you may be able to borrow legos, art supplies and puzzles, among other items.
* Go outside and jump in some puddles! Put on your rain boots and embrace the rainy weather by jumping in some puddles!
* Make origami! Use some unfolded scrap paper (or origami paper if you have some), fire up some online tutorials, and make anything from ninja stars to paper airplanes and boats (bonus: take the boat outside and sail it in a puddle!)
* Go to your local rec center! If you're lucky enough to have a recreation center close by, then a rainy day is a great day to visit, to play basketball indoors, for example.
* Take a bus or drive to a museum! 7 year olds tend to be very curious and as long as you don't overdo it, a museum can be a fun place to kill an hour or two!
Question: What is physical security?
Answer: Physical security describes security measures that are designed to deny unauthorized access to facilities, equipment, and resources and to protect personnel and property from damage or harm (such as espionage, theft, or terrorist attacks).  Physical security involves the use of multiple layers of interdependent systems that can include CCTV surveillance, security guards, protective barriers, locks, access control, perimeter intrusion detection, deterrent systems, fire protection, and other systems designed to protect persons and property.
Question: Is the performance on par with state-of-the-art methods?
Evidence: Extractive multi-document summarization (MDS) aims to summarize a collection of documents by selecting a small number of sentences that represent the original content appropriately. Typical objectives for assembling a summary include information coverage and non-redundancy. A wide variety of methods have been introduced to approach MDS.
Many approaches are based on sentence ranking, i.e. assigning each sentence a score that indicates how well the sentence summarizes the input BIBREF0 , BIBREF1 , BIBREF2 . A summary is created by selecting the top entries of the ranked list of sentences. Since the sentences are often treated separately, these models might allow redundancy in the summary. Therefore, they are often extended by an anti-redundancy filter while de-queuing ranked sentence lists.
Other approaches work at summary-level rather than sentence-level and aim to optimize functions of sets of sentences to find good summaries, such as KL-divergence between probability distributions BIBREF3 or submodular functions that represent coverage, diversity, etc. BIBREF4 
The centroid-based model belongs to the former group: it represents sentences as bag-of-word (BOW) vectors with TF-IDF weighting and uses a centroid of these vectors to represent the whole document collection BIBREF5 . The sentences are ranked by their cosine similarity to the centroid vector. This method is often found as a baseline in evaluations where it usually is outperformed BIBREF0 , BIBREF6 .
This baseline can easily be adapted to work at the summary-level instead the sentence level. This is done by representing a summary as the centroid of its sentence vectors and maximizing the similarity between the summary centroid and the centroid of the document collection. A simple greedy algorithm is used to find the best summary under a length constraint.
In order to keep the method efficient, we outline different methods to select a small number of candidate sentences from each document in the input collection before constructing the summary.
We test these modifications on the DUC2004 dataset for multi-document summarization. The results show an improvement of Rouge scores over the original centroid method. The performance is on par with state-of-the-art methods which shows that the similarity between a summary centroid and the input centroid is a well-suited function for global summary optimization.
The summarization approach presented in this paper is fast, unsupervised and simple to implement. Nevertheless, it performs as well as more complex state-of-the-art approaches in terms of Rouge scores on the DUC2004 dataset. It can be used as a strong baseline for future research or as a fast and easy-to-deploy summarization tool.
The performance is on par with state-of-the-art methods which shows that the similarity between a summary centroid and the input centroid is a well-suited function for global summary optimization.
Answer: Yes, it is.
Question: How many points did Jaromír Jágr score in the 1995-1996 season?
Evidence: In the 1994–95 season, Jágr won his first Art Ross Trophy after finishing the regular season with the most points in the NHL; he tied Eric Lindros with 70 points but won based on his 32 goals to Lindros' 29. The next year, Jágr set a record for most points, 149, by a European-born player. Both his 62 goals and 87 assists from that season still stand as career-highs. His 1995–96 totals for assists and points stand as the records for right-wingers in those categories. After the 1997–98 season, Penguins captain Ron Francis signed with the Carolina Hurricanes, leaving Jágr the Penguins' captaincy. From 1997–98 to 2000–01, Jágr would win four-straight NHL scoring titles. In 1999, he would win the Hart Memorial Trophy as the NHL's most valuable player, as well as the Lester B. Pearson Award. In 1998, he led the Czech Republic to a gold medal at the 1998 Winter Olympics.
Answer: In a record-setting year, Jaromír Jágr scored 149 points in the 1995-96 season.
Question: Tell me about the plot to Harry Potter
Answer: Harry Potter is the story of a seemingly normal 11 year old body that lives with Aunt Petunia, Uncle Vernon and cousin Dudley. He comes to find out he is in fact, not a normal boy, but a wizard, a famous wizard at that. He is offered admission at Hogwarts School of Witchcraft and Wizardry and his epic battle across 7 books against Lord Voldermort plays out. After many trails, losses and against all odds, he is victorious over Lord Voldermort.
Question: Could the authors come up with a way to use their proposed feature-time relevance maps to characterize each phenotype?
Evidence: A.13: Descriptive statistics and information of all input data features. Variables are displayed with type, de_x005f_x005f_x005fscription, units and average statistics. We separate all features according to medical literature, including vitalsign, static, serum and haem
Answer: We have updated our results and discussion section to include a more comprehensive description of each cluster. We have also added a table of summary statistics for clinical variables (e.g., demographics) over each of the learnt clusters - these further support/corroborate the description obtained from analysis of results obtained in Figure 5 and Figure 6. This new table is in the Appendix in Figure A13.
Question: What is the currency in use in the Netherlands?
Answer: The currency in use in the Netherlands is the euro.
Question: Who is the greatest golfer ever?
Answer: Most consider Jack Nicklaus the greatest golfer as he's won 18 major championships, the most of any golfer.  Major championships are considered the ultimate achievement in the sport of golf.  Jack Nicklaus also has the most runner-up finishes in major championships with 19 and the third most PGA Tour tournament wins with 73.  Many would argue that Tiger Woods is the greatest golfer of all-time with 15 major championships and more PGA Tour tournament wins (currently 82) because he played in a more modern era that was considered to have better competition than the era in which Jack Nicklaus played.  Tiger Woods was also considered to have had the largest impact on the overall popularity of the game of golf.
Question: What colour usually is the wax surrounding Edam cheese?
Answer: The colour usually is yellow or orange.