DataHammer/scimrc huggingface dataset:
Question: What classifier is the most accurate one by Rad and Barbosa's review?
Evidence: Table TABREF14 compares the accuracy reported on Dataset I for the methods suggested in BIBREF1, BIBREF4 with the accuracy obtained by our methods, as well as the latter on Dataset II, using 10-fold cross-validation in all cases. Table TABREF14 reports accuracy results of the more stringent analysis described in section SECREF13.
BIBREF4 review several controversy classifiers. The most accurate one, the Structure classifier, builds, among others, collaboration networks by considering high-level behavior of editors both in their individual forms, and their pairwise interactions. A collaboration profile containing these individual and pairwise features is built for each two interacting editors and is classified based on the agreement or disagreement relation between them. This intensive computation renders that classifier impractical. Table TABREF14 therefore also includes the most accurate classifier BIBREF4 consider practical.
As seen in Table TABREF14, for the usual 10-fold analysis the simple classifiers suggested here are on par with the best and more complex classifier reported in BIBREF4. Moreover, in the leave-one-category-out setting (Table TABREF14), accuracy indeed drops, but only marginally. We also observe the superiority of classifiers that directly access the context (NB and RNN) over classifiers that access it via word embedding (NN).
Table TABREF14 presents results obtained when models trained on Dataset I are applied to Dataset III. For this experiment we also included a BERT network BIBREF14 fine tuned on Dataset I. The Pearson correlation between the scores obtained via manual annotation and the scores generated by our automatic estimators suggests a rather strong linear relationship between the two. Accuracy was computed as for previous datasets, by taking here as positive examples the concepts receiving 6 or more positive votes, and as negative a random sample of 670 concepts out of the 1182 concepts receiving no positive vote.
Rad and Barbosa (2012) review several controversy classifiers. The most accurate one, the Structure classifier, builds, among others, collaboration networks by considering high-level behavior of editors both in their individual forms, and their pairwise interactions.
Answer: The Structure classifier.
Question: Why breakfast is so important for the day
Answer: Because you are breaking the fast after a long sleep. So you need to give something to your body.
Question: What were their results on the test set?
Evidence: Out of 43 teams our system ranked 421st with an official F1-score of 0.2905 on the test set. Although our model outperforms the baseline in the validation set in terms of F1-score, we observe important drops for all metrics compared to the test set, showing that the architecture seems to be unable to generalize well. We think these results highlight the necessity of an ad-hoc architecture for the task as well as the relevance of additional information. The work of BIBREF21 offers interesting contributions in these two aspects, achieving good results for a range of tasks that include sarcasm detection, using an additional attention layer over a BiLSTM like ours, while also pre-training their model on an emoji-based dataset of 1246 million tweets.
Out of 43 teams our system ranked 421st with an official F1-score of 0.2905 on the test set. Although our model outperforms the baseline in the validation set in terms of F1-score, we observe important drops for all metrics compared to the test set, showing that the architecture seems to be unable to generalize well.
Answer: The answers are shown as follows:
* an official F1-score of 0.2905 on the test set
Question: How difficult is it to learn how to juggle?
Answer: Learning to juggle is not difficult, but requires consistent and deliberate practice to master. Most people are capable of learning the basics if they commit to practicing the movements over the course of a few weeks. Once you learn how to juggle with three balls, you can increase the number of balls to make it more difficult.
Question: What was the Counter Reformation?
Answer: The Counter Reformation was a Catholic religious movement which was in response to the Protestant Reformation and sought to strengthen the Catholic faith.
Question: The below word pairs are all homonyms. Identify which ones are homographs, homophones, or both:

Present/Present
Spring/Spring
Flower/Flour
Answer: Present is a homograph but not a homophone. Although it is spelled the same, when used as a verb it has a different pronunciation from its noun and adjective meanings.
Spring is both a homograph and a homophone, because it is spelled and pronounced the same across all of its noun and verb forms.
Flower and Flour are homophones but not homographs, because they sound the same but are spelled differently.
Question: What dataset are the hand-designed houses from?
Evidence: Human learning occurs through interaction BIBREF0 and multimodal experience BIBREF1 , BIBREF2 . Prior work has argued that machine learning may also benefit from interactive, multimodal learning BIBREF3 , BIBREF4 , BIBREF5 , termed virtual embodiment BIBREF6 . Driven by breakthroughs in static, unimodal tasks such as image classification BIBREF7 and language processing BIBREF8 , machine learning has moved in this direction. Recent tasks such as visual question answering BIBREF9 , image captioning BIBREF10 , and audio-video classification BIBREF11 make steps towards learning from multiple modalities but lack the dynamic, responsive signal from exploratory learning. Modern, challenging tasks incorporating interaction, such as Atari BIBREF12 and Go BIBREF13 , push agents to learn complex strategies through trial-and-error but miss information-rich connections across vision, language, sounds, and actions. To remedy these shortcomings, subsequent work introduces tasks that are both multimodal and interactive, successfully training virtually embodied agents that, for example, ground language in actions and visual percepts in 3D worlds BIBREF3 , BIBREF4 , BIBREF14 .
For virtual embodiment to reach its full potential, though, agents should be immersed in a rich, lifelike context as humans are. Agents may then learn to ground concepts not only in various modalities but also in relationships to other concepts, i.e. that forks are often in kitchens, which are near living rooms, which contain sofas, etc. Humans learn by concept-to-concept association, as shown in child learning psychology BIBREF1 , BIBREF2 , cognitive science BIBREF15 , neuroscience BIBREF16 , and linguistics BIBREF17 . Even in machine learning, contextual information has given rise to effective word representations BIBREF8 , improvements in recommendation systems BIBREF18 , and increased reward quality in robotics BIBREF19 . Importantly, scale in data has proven key in algorithms learning from context BIBREF8 and in general BIBREF20 , BIBREF21 , BIBREF22 .
To this end, we present HoME: the Household Multimodal Environment (Figure 1 ). HoME is a large-scale platform for agents to navigate and interact within over 45,000 hand-designed houses from the SUNCG dataset BIBREF23 . Specifically, HoME provides:
HoME is a general platform extensible to many specific tasks, from reinforcement learning to language grounding to blind navigation, in a real-world context. HoME is also the first major interactive platform to support high fidelity audio, allowing researchers to better experiment across modalities and develop new tasks. While HoME is not the first platform to provide realistic context, we show in following sections that HoME provides a more large-scale and multimodal testbed than existing environments, making it more conducive to virtually embodied learning in many scenarios.
To this end, we present HoME: the Household Multimodal Environment (Figure 1 ). HoME is a large-scale platform for agents to navigate and interact within over 45,000 hand-designed houses from the SUNCG dataset.
Answer: SUNCG dataset.
Question: Can the framework generate NL be understood by lay users?
Evidence: In this paper, we presented LD2NL, a framework for verbalizing SW languages, especially on RDF and OWL while including the SPARQL verbalization provided by SPARQL2NL. Our evaluation with 86 persons revealed that our framework generates NL that can be understood by lay users. While the OWL verbalization was close to NL, the RDF was less natural but still sufficient to convey the meaning expressed by the corresponding set of triples. In future work, we aim to extend LD2NL to verbalize the languages SWRL BIBREF23 and SHACL BIBREF24.
Our evaluation with 86 persons revealed that our framework generates NL that can be understood by lay users.
Answer: Yes, it can.
Question: Classify the below items based on who owns them. Google or Microsoft.
Bard, ChatGPT, Chrome, Bing
Answer: Bard, Chrome - Google
ChatGPT, Bing - Microsoft
Question: Give me a 4 word summary of Moby Dick, which rhymes.
Answer: Whale tale. Ahab fail.
Question: What city in the United States is known for its Mardi Gras celebrations?
Answer: New Orleans is famous for its celebrations of Mardi Gras
Question: Name the place in New Zealand, where a volcano erupted?
Answer: Whakaari (also known as White Island)
Question: What books did Brene Brown write?
Answer: Brene Brown has written several books that are based around personal growth, vulnerability, and leadership. Some of the books she has written include The Gifts of Imperfection, Dare to Lead, Daring Greatly, Braving the Wilderness and I Thought It Was Me But It Wasn't
Question: Extract the awards that Ian McEwan has won and list them in chronological order (oldest to most recent) using bullets, with associated dates in parentheses.
Evidence: Ian Russell McEwan, CBE, FRSA, FRSL (born 21 June 1948) is an English novelist and screenwriter. In 2008, The Times featured him on its list of "The 50 greatest British writers since 1945" and The Daily Telegraph ranked him number 19 in its list of the "100 most powerful people in British culture".

McEwan began his career writing sparse, Gothic short stories. His first two novels, The Cement Garden (1978) and The Comfort of Strangers (1981), earned him the nickname "Ian Macabre". These were followed by three novels of some success in the 1980s and early 1990s. His novel Enduring Love was adapted into a film of the same name. He won the Booker Prize with Amsterdam (1998). His next novel, Atonement, garnered acclaim and was adapted into an Oscar-winning film featuring Keira Knightley and James McAvoy. His later novels have included The Children Act, Nutshell, and Machines Like Me. He was awarded the 1999 Shakespeare Prize, and the 2011 Jerusalem Prize.
Answer: -Booker Prize (1998)
-Shakespeare Prize (1999)
-Jerusalem Prize (2011)
Question: Whether the proposed approach leads to the state of the art results?
Evidence: Previous work on multimodal machine translation has shown that visual information is only needed in very specific cases, for example in the presence of ambiguous words where the textual context is not sufficient. As a consequence, models tend to learn to ignore this information. We propose a translate-and-refine approach to this problem where images are only used by a second stage decoder. This approach is trained jointly to generate a good first draft translation and to improve over this draft by (i) making better use of the target language textual context (both left and right-side contexts) and (ii) making use of visual context. This approach leads to the state of the art results. Additionally, we show that it has the ability to recover from erroneous or missing words in the source language.
This approach leads to the state of the art results.
Answer: Yes.
Question: How is FLC task evaluated?
Evidence: FLC is a composition of two subtasks: the identification of the propagandist text fragments and the identification of the techniques used (18-way classification task). While F$_1$ measure is appropriate for a multi-class classification task, we modified it to account for partial matching between the spans; see BIBREF10 for more details. We further computed an F$_1$ value for each propaganda technique (not shown below for the sake of saving space, but available on the leaderboard).
SLC is a binary classification task with imbalanced data. Therefore, the official evaluation measure for the task is the standard F$_1$ measure. We further report Precision and Recall.
The results on the test set for the SLC task are shown in Table TABREF33, while Table TABREF34 presents the results on the development set at the end of phase 1 (cf. Section SECREF6). The general decrease of the F$_1$ values between the development and the test set could indicate that systems tend to overfit on the development set. Indeed, the winning team ltuorp chose the parameters of their system both on the development set and on a subset of the training set in order to improve the robustness of their system.
Tables TABREF36 and TABREF41 report the results on the test and on the development sets for the FLC task. For this task, the results tend to be more stable across the two sets. Indeed, team newspeak managed to almost keep the same difference in performance with respect to team Antiganda. Note that team MIC-CIS managed to reach the third position despite never having submitted a run on the development set.
While F1 measure is appropriate for a multi-class classification task, we modified it to account for partial matching between the spans;  see (Da San Martino et al., 2019) for more details. We further computed an F1 value for each propaganda technique (not shown below for the sake of saving space, but available on the leaderboard).
Answer: They modified F1 measuret to account for partial matching between the spans and further computed an F1 value for each propaganda technique.
Question: can you recommend fun activities to enjoy in Austin in summer?
Answer: Summer can be hot in Austin, with historical highest temperatures went above 100 Farheiths. Outdoor activities are challenging in the torching sun and steaming air. Luckily, Austin, as part of the Hill Country, has a lot of hiking trails with shades and mild elevation. Hiking in early morning is enjoyable if you are an early bird. You can still enjoy outdoors in summer with water. Kayaking, SUPs, tubing, canoeing, swimming, and boat tours are available at public parks or with hosting companies at Lake Travis. Alternatively, enjoy cool AC empowered indoor gyms and playground in July or August.
Question: Is it better to invest in the stock market or to keep money in a savings account?
Answer: There are key differences between investing in the stock market versus keeping money in a savings account. Savings accounts can be FDIC insured up to $250k (although there are services that can increase this limit such as Wealthfront) and thus are extremely safe places to store money, but these accounts generally have very low interest rates and thus the money will not grow quickly (or at all, compared to inflation). Generally it is recommended to keep an emergency fund available in savings accounts as they may need to be quickly accessible. 

The stock market works differently - you are purchasing shares of a company, and ideally that company grows over time, thus increasing the value of the underlying stocks. People generally invest in the stock market in order to grow their money over time, although it is recommended to measure the success or failure of investments over a long time period (greater than 10 years). The broader US stock market has historically grown nearly 10%/year on average, although many years significantly deviate from that growth rate.
Question: Identify which instrument is string or percussion: Taiko, Vlier
Answer: Vlier is string, Taiko is percussion.
Question: Output a table in CSV format of the games mentioned and how many points Ivey scored
Evidence: Early in his freshman season, Ivey missed five games with a foot injury. On January 19, 2021, he made a game-winning three-pointer with five seconds left as part of a 15-point performance in a 67–65 win over Ohio State. On March 19, Ivey scored a season-high 26 points in a 78–69 overtime loss to North Texas at the first round of the NCAA tournament. As a freshman, he averaged 11.1 points and 3.3 rebounds per game, earning Big Ten All-Freshman Team honors.

On November 12, 2021, Ivey scored 27 points in a 92–67 win over Indiana State. On January 30, 2022, he scored 21 points and hit the game-winning three-pointer with 0.6 seconds remaining in an 81–78 win over Ohio State. As a sophomore, he averaged 17.3 points, 4.9 rebounds and 3.1 assists per game. Ivey was named to the First Team All-Big Ten as well as the All-American Second Team. On March 31, 2022, Ivey declared for the 2022 NBA draft, forgoing his remaining college eligibility. He was a projected top five pick in the draft.
Answer: Game Summary,Points Scored by Ivey
67–65 win over Ohio State,15
78–69 overtime loss to North Texas,26
92–67 win over Indiana State,27
81–78 win over Ohio State,21
Question: Classify these MLB teams as either National League or American League teams: New York Mets, St. Louis Cardinals, Los Angeles Dodgers, Arizona Diamondbacks, Tampa Bay Rays, New York Yankees, Houston Astros, Oakland A's
Answer: National League: New York Mets, St. Louis Cardinals, Los Angeles Dodgers, Arizona Diamondbacks
American League: Tampa Bay Rays, New York Yankees, Houston Astros, Oakland A's
Question: What is the best way to define a data&AI strategy?
Answer: Translate your business and digital strategy into your data and AI vision and strategy highlighting the biggest opportunity areas optimizing your current business as well as new innovative businesses utilizing AI and data.

Identify the business processes (product development, production, sales & marketing, supply chain, pricing, HR, finance, etc.) where you want to use data and AI.

Understand the current state of your data and AI capabilities.

Describe the target state for your business processes once data and AI capabilities have been deployed.

Define new data-driven business and product ideas.

Define your execution roadmap, including investments.

Execute the first data and AI use cases by creating your AI playbook, aiming at production readiness.

Automate and scale up operations
Question: What is "Disko"?
Evidence: "Disko" (Slovene pronunciation: [ˈdíːskɔ]) is a 2022 song by Slovenian pop band Last Pizza Slice. The song represented Slovenia in the Eurovision Song Contest 2022 in Turin, Italy, after winning EMA 2022, Slovenia's national final.

Release
The song was released on 26 November 2021, along with all other songs competing in EMA 2022. It was officially released to streaming services on 1 April.

Music video
An animated music video of "Disko" would come out on 11 April, with artwork by Manca Matelič, a school classmate of the band, and Matevž Bervar. The video features a man getting dumped by his girlfriend at a nightclub. The man ends up being depressed, drinking at the nightclub. One day, while seeing his ex-girlfriend kiss her boyfriend at a bridge, the man falls over into a river. While it is unknown if the man drowned or hallucinated, underwater, he eventually meets another girl, and becomes happy again.[citation needed]

The music video is inspired by the lead singer, Filip Vidušin, having a real life experience of getting dumped at a disco and watching his ex-girlfriend dance with another man.
Answer: "Disko" is a 2022 song by Slovenian pop band Last Pizza Slice.
Question: Who is the most decorated olympian of all time?
Answer: Michael Phelps is the most decorated olympian winning a total of 28 medals.
Question: Who is using Spark in production?
Answer: As of 2016, surveys show that more than 1000 organizations are using Spark in production. Some of them are listed on the Powered By page and at the Spark Summit.
Question: What is Szalay doing these days?
Evidence: István Szalay (22 March 1944 – 1 September 2022) was a Hungarian mathematician and politician. A member of the Hungarian Socialist Party, he served in the National Assembly from 1998 to 2002. Prior to that, he was mayor of Szeged from 1994 to 1998.

Szalay died on 1 September 2022, at the age of 78.
Answer: Sadly, István Szalay passed away on 1 September 2022, at the age of 78. And hence to answer your question, he is dead and does't exists anymore.
Question: Summarize what electoral college does in USA presidential election
Evidence: The United States Electoral College is the group of presidential electors required by the Constitution to form every four years for the sole purpose of appointing the president and vice president. Each state and the District of Columbia appoints electors pursuant to the methods described by its legislature, equal in number to its congressional delegation (representatives and senators). Federal office holders, including senators and representatives, cannot be electors. Of the current 538 electors, an absolute majority of 270 or more electoral votes is required to elect the president and vice president. If no candidate achieves an absolute majority there, a contingent election is held by the House of Representatives to elect the president and by the Senate to elect the vice president.
The states and the District of Columbia hold a statewide or districtwide popular vote on Election Day in November to choose electors based upon how they have pledged to vote for president and vice president, with some state laws proscribing faithless electors. All states except Maine and Nebraska use a party block voting, or general ticket method, to choose their electors, meaning all their electors go to one winning ticket. Maine and Nebraska choose one elector per congressional district and two electors for the ticket with the highest statewide vote. The electors meet and vote in December, and the inauguration of the president and vice president takes place in January.
Answer: Each states appoints electors based on methods by their legislature. 
Number of electors from each state are same as number of representatives from that state.
Candidate needs 270 electoral votes out of 538 to win presidential election.
All electors from state cast each of their vote to whoever received most votes in that state.
Maine and Nebraska can split their electoral votes based on whoever wins their district.
If no candidate gets 270 votes or higher then House of Representatives meets to elect President and Vice President.
Question: Based on this paragraph about Brazilian jiu-jitsu. which martial arts influenced Jiu-Jitsu.
Evidence: BJJ eventually came to be its own defined combat sport through the innovations, practices, and adaptation of Gracie jiu-jitsu and Judo, and became an essential martial art for modern MMA. Governing bodies such as the IBJJF work worldwide, and set the rules and standards to be held in sport BJJ competitions.
Answer: Jiu-jitsu and Judo
Question: How are clouds formed?
Answer: It all begins with aerosols. Aerosols are tiny airborne particles typically from natural sources such as dust from soil or volcanic ash, sea salt, etc or artificial sources such as carbon from fossil fuels. These aerosols are light enough to be airborne for long periods of time or only a few hours. These serve as condensation nuclei for evaporated water that rises and cools. These aerosols act as a magnet for the vapor and allow it to condense around it and thus form water droplets. A large amount of these water droplets is what makes up a cloud.
Question: Classify each of the following as being related to Google or Microsoft: Xbox, Waymo, Surface Pro, Youtube, Bing, Chrome
Answer: Xbox: Microsoft
Waymo: Google
Surface Pro: Microsoft
Youtube: Google
Bing: Microsoft
Chrome: Google
Question: Find an item from each category bellow that somehow relates to a tangerine.

place:
animal
vehicle
feeling
food
tech
song
movie
Answer: place: tangier
animal: tiger
vehicle: Cinderella's carriage 
feeling: summer with family
food: marmalade
tech: ear pods
song: tangerine, Led Zeppelin
movie: Eternal sunshine of the spotless mind