DataHammer/scimrc huggingface dataset:
Question: What is the oldest higher learning institution in the United States
Evidence: Harvard University is a private Ivy League research university in Cambridge, Massachusetts. Founded in 1636 as Harvard College and named for its first benefactor, the Puritan clergyman John Harvard, it is the oldest institution of higher learning in the United States and is widely considered to be one of the most prestigious universities in the world.
Answer: The oldest higher learning institution in the United States is Harvard University, which is widely considered the most prestigious university in the world.
Question: How should I think about ways to arrange a desk in a home office
Answer: There are several ways to arrange a desk in a home office. A few guiding principles (based on the space and how you'll use your desk) can help guide you along the way. 

* If you're frequently on camera for video calls you'll want to consider what people will see in your background. Avoid clutter and too much distraction, but also feel free to use that part of the office to express yourself professionally. An interesting painting or a few professional accolades can be a good conversation starters.

* Bright windows can be great for creativity but having these directly behind you when on video calls can give you a whitewashed look that's not ideal. Ideally, a window would be in front of you to not only cast your face in a good light, but also to give you a nice view as you work. If you can't position a window on front of your desk, you could always invest in good artificial lighting (e.g., a ring light) to help with video calls. 

* Avoid having positioning your desk so your back is directly in front of the office entrance. If you have line of site to all entrances / exits you'll likely feel more in control while working, which can make you more productive. 

* Position your desk so you have easy access to everything you'd need for work. Frequently used reference materials, papers, writing supplies, etc. should all be within arms length so as not to disrupt your "flow" while working.
Question: Where is the Burg Lockenhaus located
Evidence: Burg Lockenhaus (Hungarian Léka) is a castle and medieval fortress in the Güns Valley in the southeastern part of Lockenhaus, in Burgenland, eastern Austria. Burg Lockenhaus is 368 metres (1,207 ft) above sea level. The castle was built in Romanesque and Gothic architectural styles around 1200, and was initially called "Leuca" or Léka. It is part of the Naturpark Geschriebenstein.

Geography
The castle is in the Güns Valley, set amidst a hilly terrain in eastern Austria, near the Hungarian border towards Kőszeg. It is in the southeastern part of the town of Lockenhaus, roughly 120 kilometres (75 mi) south of Vienna and roughly the same distance by road northeast of Graz.[citation needed] It was built on the spur of a hill, which is now called the Castle Hill. It can be reached by express bus service along the Eisenstadter Bundestrasse. A lake lies immediately to the east of the castle.
Answer: Burg Lockenhaus (Hungarian Léka) is a castle and medieval fortress in the Guens Valley in the southeastern part of Lockenhaus, in Burgenland, eastern Austria. Burg Lockenhaus is 368 metres (1,207 ft) above sea level. The castle was built in Romanesque and Gothic architectural styles around 1200, and was initially called "Leuca" or Léka. It is part of the Naturpark Geschriebenstein.
Question: Which is a species of fish? Dolphin or Dolphin fish
Answer: Dolphin fish
Question: Q: What do I do if I get a rash or other reaction to hand sanitizer? What do I do if I have been exposed to contaminated hand sanitizer?
Answer: A: Call your doctor if you experience a serious reaction to hand sanitizer. People who have been exposed to contaminated hand sanitizer and are experiencing symptoms should seek immediate medical treatment for potential reversal of toxic effects.

The FDA encourages consumers and health care professionals to report adverse events experienced with the use of hand sanitizers to the FDA’s MedWatch Adverse Event Reporting program:

Complete and submit the report online; or
Download and complete the form, then submit it via fax at 1-800-FDA-0178.
Include as much information as you can about the product that caused the reaction, including the product name, the manufacturer, and the lot number (if available).

See Q&A for Consumers: Hand Sanitizers and COVID-19 and Safely Using Hand Sanitizer for more information.
Question: What are the names of all Depeche Mode albums?
Answer: Speak & Spell, released in 1981.
A Broken Frame, released in 1982.
Construction Time Again, released in 1983.
Some Great Reward, released in 1984.
Black Celebration, released in 1986.
Music for the Masses, released in 1987.
Violator, released in 1990.
Songs of Faith and Devotion, released in 1993.
Ultra, released in 1997.
Exciter, released in 2001.
Playing the Angel, released in 2005.
Sounds of the Universe, released in 2009.
Delta Machine, released in 2013.
Spirit, released in 2017.
Memento Mori, released in 2023.
Question: What are some of the sight seeing and outdoor activities to do in Portugal, Spain
Answer: Day 1: Arrival in Lisbon
- Transfer from the airport to the hotel (8.6 miles/14 km)

Day 2: Lisbon
- Visit to Belém Tower (5.5 miles/9 km)
- Jerónimos Monastery
- St. George's Castle
- Alfama neighborhood 

Day 3: Sintra
- Visit to Pena Palace (18.7 miles/30 km)
- Sintra National Palace
- Cabo da Roca (14.6 miles/23.5 km)

Day 4: Cascais
- Beach day in Cascais (16.8 miles/27 km)
- Visit to Boca do Inferno
- Cascais Marina

Day 5: Óbidos
- Visit to Óbidos Castle (52.8 miles/85 km)
- Walk through the village
- Visit to Alcobaça Monastery (22.8 miles/37 km)

Day 6: Nazaré
- Visit to Nazaré beach (30.7 miles/49.5 km)
- Cable car ride
- Visit to the Chapel of Our Lady of Nazaré

Day 7: Coimbra
- Visit to Coimbra University (68.3 miles/110 km)
- Walk through the historic center
- Visit to the Old Cathedral

Day 8: Aveiro
- Boat ride through the canals of Aveiro (44.7 miles/72 km)
- Visit to the Aveiro Cathedral
- Walk through the Fisherman's Quarter

Day 9: Porto
- Visit to the Ribeira neighborhood (46.6 miles/75 km)
- Climb the Clérigos Tower
- Visit to the São Bento train station
- Tour of the Port wine cellars

Day 10: Departure from Porto
- Transfer from the hotel to the airport (10.4 miles/17 km)
Question: What is OAuth 2.0?
Answer: OAuth 2.0, which stands for “Open Authorization”, is a standard designed to allow a website or application to access resources hosted by other web apps on behalf of a user. It replaced OAuth 1.0 in 2012 and is now the de facto industry standard for online authorization.
Question: What do DFNs differ from most state-of-the-art models?
Evidence: This paper presents a novel neural model - Dynamic Fusion Network (DFN), for machine reading comprehension (MRC). DFNs differ from most state-of-the-art models in their use of a dynamic multi-strategy attention process, in which passages, questions and answer candidates are jointly fused into attention vectors, along with a dynamic multi-step reasoning module for generating answers. With the use of reinforcement learning, for each input sample that consists of a question, a passage and a list of candidate answers, an instance of DFN with a sample-specific network architecture can be dynamically constructed by determining what attention strategy to apply and how many reasoning steps to take. Experiments show that DFNs achieve the best result reported on RACE, a challenging MRC dataset that contains real human reading questions in a wide variety of types. A detailed empirical analysis also demonstrates that DFNs can produce attention vectors that summarize information from questions, passages and answer candidates more effectively than other popular MRC models.
This paper presents a novel neural model - Dynamic Fusion Network (DFN), for machine reading comprehension (MRC). DFNs differ from most state-of-the-art models in their use of a dynamic multistrategy attention process, in which passages, questions and answer candidates are jointly fused into attention vectors, along with a dynamic multi-step reasoning module for generating answers.
Answer: Their use of a dynamic multistrategy attention process, in which passages, questions and answer candidates are jointly fused into attention vectors, along with a dynamic multi-step reasoning module for generating answers.
Question: Categorize each of the following instruments as either string or keyboard: Guitar, Violin, piano, harmonium, cello, accordion, banjo
Answer: Guitar - String
Violin - String
piano - keyboard
harmonium - keyboard
cello - string
accordion - keyboard
banjo - string
Question: How many seasons of Greatest American Hero were there?
Answer: There were three seasons of The Greatest American Hero.
Question: Give me a list of books that are long and hard to read. The sort of books with which I could impress someone who read a lot.
Answer: When talking to someone well read, I would go with some of the classics of literature. The following books require a very detailed read in order to be able to understand them, due to the complex topics they analyze. They are long, but also considered masterpieces:

- "Crime and Punishment" by Dostoievsky
- "Ulysses" by James Joyce
- "The Magic Mountain" by Thomas Mann
- "Gravity's Rainbow" by Thomas Pynchon
- "Don Quixote" by Miguel de Cervantes
- "Infinite Jest" by David Foster Wallace
Question: Why do people move/sway during music?
Answer: Scientists believe we are born with a sense of rhythm and our bodies naturally react and behave to the sound of music in different ways.
Question: What do authors use to transform P, Q, and C into word embedding?
Evidence: In this question answering task, a reading passage , a query and several answer choices are given. P denotes the passage, Q denotes query and C denotes one of the multiple choices. The target of the model is to choose a correct answer A from multiple choices based on informations of P and Q.
Fig. FIGREF1 is the pipeline overview of QACNN. First, we use embedding layer to transform P, Q, and C into word embedding. Then the compare layer generates passage-query similarity map INLINEFORM0 and passage-choice similarity map INLINEFORM1 . The following part is the main component of QACNN. It consists of two-staged CNN architecture. The first stage projects word-level feature into sentence-level, and the second stage projects sentence-level feature into passage-level. Moreover, we apply query-based attention mechanism to each stage on the basis of INLINEFORM2 feature at word level and sentence level respectively. After QACNN Layer, we obtain each choice answer feature. Finally, a prediction layer collects output information from every choice feature and returns the most possible answer.
First, we use embedding layer to transform P, Q, and C into word embedding.
Answer: Embedding layer.
Question: What is a Flat Earth Society
Answer: Flat Earth Society is a group of like minded people who believe the earth to be flat rather than round. Although science has proven the existence of our earth as a circular mass orbiting the sun in the solar system, the Flat Earthers firmly believe it to be a propaganda and continue to hold the belief that the earth is actually flat and not round.
Question: Tell me whether the following European languages are in the Indo-European language family or not: Spanish, English, Basque, Finnish, Romanian, Hungarian, and Catalan.
Answer: Spanish, Romanian, and Catalan are all Indo-European languages classified within the Romance branch of Indo-European languages.  English and German are both Indo-European languages classified within the Germanic branch of Indo-European languages.  Basque, Finnish, and Hungarian are not Indo-European languages.  Basque is a language isolate and is not known to be related to any other living language.  Finnish and Hungarian are Uralic languages and are not related to the Indo-European languages.
Question: Should differential privacy be used in the U.S. census?
Answer: I disagree with the US Census Bureau in its use of differential privacy for reasons as follow. The main purpose of the US Census is enumeration – to correctly count the population such that resource distribution can be performed smoothly and properly in the future. The use of differential privacy essentially undermines this goal. Although populations at the state level would remain true to the raw data, those at the town level could be subject to much higher variances. For example, the New York Times article “Changes to the Census Could Make Small Towns Disappear” exemplifies how differential privacy could compromise the enumerative purpose of the US Census. Native American towns that are much less populated than the urban districts could see their population numbers being halved by the DP algorithm. In addition, these incorrect numbers for Native Americans mean more than a mere calculation mistake – it could bring real-world consequences like reduced fundings or inadequate political representation. Yet, isn’t the US Census counting the population such that everyone can receive federal resources and form political constituency equally and equitably? Therefore, the use of differential privacy essentially negates the Census’s purpose.

Besides the more material concern illustrated above, I argue that the use of differential privacy could also lead to a much more social and cultural issue – representation. The New York Times article has revealed that our society has adopted algorithms that always attend to the majority at the expense of the minority, and such logic behind the algorithmic design would push the representation issue into a vicious cycle. Native American people, whose land was brutally taken away and colonized, have been historically rendered as a minority group in the society. All talks on land reparations aside, the US Census Bureau has designed and passed after checks an algorithm that diminishes their very existence on the spreadsheet. What does this imply about the logic behind the implementation of differential privacy? If the Census Bureau is fully aware that most of the Native American towns are rather sparsely populated, and the algorithm to preserve differential privacy would lead to high variances for estimation of small populations, what does the implementation of this algorithm imply? That this group of people are fine with not being represented in the final headcount, even if they have spent time and money in the process? This show of negligence again invalidates the use of differential privacy in the US Census.
Question: Does the fact that GCNs can perform well on this tell us that the task is simpler than previously thought?
Evidence: We see that gated architectures almost always outperform recurrent, attention and linear models BoW, TFIDF, PV. This is largely because while training and testing on same domains, these models especially recurrent and attention based may perform better. However, for Domain Adaptation, as they lack gated structure which is trained in parallel to learn importance, their performance on target domain is poor as compared to gated architectures. As gated architectures are based on convolutions, they exploit parallelization to give significant boost in time complexity as compared to other models. This is depicted in Table 1 .
We find that gated architectures vastly outperform non gated CNN model. The effectiveness of gated architectures rely on the idea of training a gate with sole purpose of identifying a weightage. In the task of sentiment analysis this weightage corresponds to what weights will lead to a decrement in final loss or in other words, most accurate prediction of sentiment. In doing so, the gate architecture learns which words or n-grams contribute to the sentiment the most, these words or n-grams often co-relate with domain independent words. On the other hand the gate gives less weightage to n-grams which are largely either specific to domain or function word chunks which contribute negligible to the overall sentiment. This is what makes gated architectures effective at Domain Adaptation.
We see that gated architectures almost always outperform recurrent, attention and linear models BoW, TFIDF, PV. This is largely because while training and testing on same domains, these models especially recurrent and attention based may perform better. However, for Domain Adaptation, as they lack gated structure which is trained in parallel to learn importance, their performance on target domain is poor as compared to gated architectures. As gated architectures are based on convolutions, they exploit parallelization to give significant boost in time complexity as compared to other models.
The effectiveness of gated architectures rely on the idea of training a gate with sole purpose of identifying a weightage. In the task of sentiment analysis this weightage corresponds to what weights will lead to a decrement in final loss or in other words, most accurate prediction of sentiment. In doing so, the gate architecture learns which words or n-grams contribute to the sentiment the most, these words or n-grams often co-relate with domain independent words. On the other hand the gate gives less weightage to n-grams which are largely either specific to domain or function word chunks which contribute negligible to the overall sentiment. This is what makes gated architectures effective at Domain Adaptation.
Answer: No.
Question: Of the following, which are characters from the TV show "I Love Lucy:" Lucy Ricardo, Ethel Mertz, Donald Trump, John Fitzgerald Kennedy, Ricky Ricardo, Fred Mertz, Batman, John Smith
Answer: Lucy Ricardo, Ethel Mertz, Ricky Ricardo, Fred Mertz
Question: Which characters belong to DC or Marvel Universe? Magneto, Dr. Polaris
Answer: Dr. Polaris is DC, Magneto is Marvel
Question: Where was the 2018 UCI Track Cycling World Championships held?
Evidence: The 2018 UCI Track Cycling World Championships were the World Championships for track cycling in 2018. They took place in the Netherlands at the Omnisport Apeldoorn from 28 February to 4 March 2018.
Answer: The UCI Track Cycling World Championships were held in Omnisport Apeldoorn velodrome, in the Netherlands.
Question: Please write a bulleted list of the key people involved in the construction of the Amsterdam Centraal station, and their role in the project.
Evidence: Amsterdam Centraal was designed by Pierre Cuypers, who is also known for his design of the Rijksmuseum in Amsterdam. While Cuypers was the principal architect, it is believed that he focused mostly on the decoration of the station building and left the structural design to railway engineers. The station was built by contractor Philipp Holzmann. The new central station replaced Amsterdam Willemspoort Station, which had closed in 1878, as well as the temporary Westerdok Station used from 1878 to 1889. The idea for a central station came from Johan Rudolph Thorbecke, then the Netherlands Minister of the Interior and responsible for the national railways, who, in 1884, laid two proposals before the Amsterdam municipal council. In the first proposal, the station would be situated between the Leidseplein and the Amstel river. In the other, it would be built in the open harbour front allowing for the station to be connected to the existing main lines in the area to the west and the south, but also to a projected new northern line.
Answer: The key people involved in the construction of Amsterdam Centraal station were:
- Pierre Cuypers: designer
- Philipp Holzmann: building contractor
- Johan Rudolph Thorbecke: proposer
Question: What does costco do?
Answer: Costco wholesale is a membership warehouse that offers direct to consumer pricing for products bought in bulk.  The majority of Costco's revenue is generated from memberships not from the products they sell.  They also offer brand-name merchandise at steeply discounted prices.  With a Costco membership you can also purchase products online directly and have then shipped directly to you.  Competitors to Costco are Sam's Club, Walmart, Amazon, Kroger, HEB, Home Depot, and Lowes.
Question: Name five professional sports teams in the state of New York.
Answer: Five professional sports teams in the state of New York are the New York Yankees, New York Mets, New York Islands, Brooklyn Nets, and New York Knicks.
Question: What is India's rank in Global Gender Gap Index 2022
Answer: 135 out of 146 countries
Question: What architecture do they propose?
Evidence: Named Entity Recognition (NER) is an important step in most of the natural language processing (NLP) pipelines. It is designed to robustly handle proper names, which is essential for many applications. Although a seemingly simple task, it faces a number of challenges in noisy datasets and it is still considered an emerging research area BIBREF0 , BIBREF1 . Despite recent efforts, we still face limitations at identifying entities and (consequently) correctly classifying them. Current state-of-the-art NER systems typically have about 85-90% accuracy on news text - such as articles (CoNLL03 shared task data set) - but they still perform poorly (about 30-50% accuracy) on short texts, which do not have implicit linguistic formalism (e.g. punctuation, spelling, spacing, formatting, unorthodox capitalisation, emoticons, abbreviations and hashtags) BIBREF2 , BIBREF3 , BIBREF4 , BIBREF1 . Furthermore, the lack of external knowledge resources is an important gap in the process regardless of writing style BIBREF5 . To face these problems, research has been focusing on microblog-specific information extraction techniques BIBREF2 , BIBREF6 .
In this paper, we propose a joint clustering architecture that aims at minimizing the current gap between world knowledge and knowledge available in open domain knowledge bases (e.g., Freebase) for NER systems, by extracting features from unstructured data sources. To this aim, we use images and text from the web as input data. Thus, instead of relying on encoded information and manually annotated resources (the major limitation in NER architectures) we focus on a multi-level approach for discovering named entities, combining text and image features with a final classifier based on a decision tree model. We follow an intuitive and simple idea: some types of images are more related to people (e.g. faces) whereas some others are more related to organisations (e.g. logos), for instance. This principle is applied similarly to the text retrieved from websites: keywords for search engines representing names and surnames of people will often return similarly related texts, for instance. Thus, we derive some indicators (detailed in sec:finalclassifier which are then used as input features in a final classifier.
To the best of our knowledge, this is the first report of a NER architecture which aims to provide a priori information based on clusters of images and text features.
In this paper, we propose a joint clustering architecture that aims at minimizing the current gap between world knowledge and knowledge available in open domain knowledge bases (e.g., Freebase) for NER systems, by extracting features from unstructured data sources.
Answer: A joint clustering architecture that aims at minimizing the current gap between world knowledge and knowledge available in open domain knowledge bases (e.g., Freebase) for Named Entity Recognition (NER) systems, by extracting features from unstructured data sources.
Question: What are the branches of the United States Government?
Answer: The branches of the United States Government are the Judicial, Legislative, and Executive. The Judicial Branch evaluates the laws, and is made of the Supreme Court and lower courts. The Legislative Branch makes the laws, and is made of the Senate and the House of Representatives. The Executive branch carries out and enforces the law, and is made of the President, Vice President, Cabinet, and several government agencies.