DataHammer/scimrc huggingface dataset:
Question: How many methods are used for the investigation?
Evidence: Shallow syntax provides an approximation of phrase-syntactic structure of sentences; it can be produced with high accuracy, and is computationally cheap to obtain. We investigate the role of shallow syntax-aware representations for NLP tasks using two techniques. First, we enhance the ELMo architecture to allow pretraining on predicted shallow syntactic parses, instead of just raw text, so that contextual embeddings make use of shallow syntactic context. Our second method involves shallow syntactic features obtained automatically on downstream task data. Neither approach leads to a significant gain on any of the four downstream tasks we considered relative to ELMo-only baselines. Further analysis using black-box probes confirms that our shallow-syntax-aware contextual embeddings do not transfer to linguistic tasks any more easily than ELMo's embeddings. We take these findings as evidence that ELMo-style pretraining discovers representations which make additional awareness of shallow syntax redundant.
First, we enhance the ELMo architecture (Peters et al.,2018b) to allow pretraining on predicted shallow syntactic parses, instead of just raw text, so that contextual embeddings make use of shallow syntactic context. Our second method involves shallow syntactic features obtained automatically on downstream task data.
Answer: Two methods. They enhance the ELMo architecture to allow pretraining on predicted shallow syntactic parses and their second method involves shallow syntactic features obtained automatically on downstream task data.
Question: What is the source or cause of the Sun’s light?
Answer: Much like other stars the Sun is powered by nuclear reactions. The process of nuclear fusion takes place in the Sun’s core. The intense pressure and temperature at the core causes nuclear fusion - in this case hydrogen atoms fusing to create helium this process releases energy. The energy is emitted as gamma rays which travel slowly from the Sun’s core to the outer region. During the rise to the surface gamma rays collide with electrons degrading in temperature and energy to finally emerge  as visible radiation - this is the light Sun produces.
Question: Who is the lead singer of the band elbow?
Answer: Guy Garvey is the lead singer of elbow.
Question: What is the video game Diablo
Answer: Diablo is a action time playing dungeon crawler video game series developed by Blizzard entertainment. The series is made up of multiple games, Diablo, Diablo II, Diablo III, Diablo immortal and soon Diablo IV
Question: Describe ZMOT (Zero moment of truth) and how it differs from the 3-step model of marketing that was prevalent at the time of its introduction.
Answer: The 3-step model (ZMOT, FMOT, SMOT) of marketing from P&G begins with the consumer discovering a product via an Ad or hearing it from other sources like friends or colleagues. This trigger moment is followed by (FMOT) the first moment of truth where consumers are at the shelf, looking to buy, touch and feel the product and evaluate competitive offerings on the adjacent frames. The last step is the (SMOT) second moment of truth, where consumers purchase and start using the products.  

ZMOT (Zero moment of truth) is the time between the trigger and FMOT. It is when the consumers learn more about the products before they appear on the shelf. ZMOT is the pre-shopping experience where consumers can watch YouTube videos of the product, read Amazon reviews, and have a complete product experience before buying.
Question: Are the following items candy bars or gum: trident, Twix, hubba bubba, snickers, three musketeers, and wrigleys.
Answer: Three musketeers, Twix, and snickers are candy bars, and trident, hubba bubba, and wrigleys are gum.
Question: What does the largest Arabic offensive language dataset include?
Evidence: Disclaimer: Due to the nature of the paper, some examples contain highly offensive language and hate speech. They don't reflect the views of the authors in any way, and the point of the paper is to help fight such speech. Much recent interest has focused on the detection of offensive language and hate speech in online social media. Such language is often associated with undesirable online behaviors such as trolling, cyberbullying, online extremism, political polarization, and propaganda. Thus, offensive language detection is instrumental for a variety of application such as: quantifying polarization BIBREF0, BIBREF1, trolls and propaganda account detection BIBREF2, detecting the likelihood of hate crimes BIBREF3; and predicting conflict BIBREF4. In this paper, we describe our methodology for building a large dataset of Arabic offensive tweets. Given that roughly 1-2% of all Arabic tweets are offensive BIBREF5, targeted annotation is essential for efficiently building a large dataset. Since our methodology does not use a seed list of offensive words, it is not biased by topic, target, or dialect. Using our methodology, we tagged 10,000 Arabic tweet dataset for offensiveness, where offensive tweets account for roughly 19% of the tweets. Further, we labeled tweets as vulgar or hate speech. To date, this is the largest available dataset, which we plan to make publicly available along with annotation guidelines. We use this dataset to characterize Arabic offensive language to ascertain the topics, dialects, and users' gender that are most associated with the use of offensive language. Though we suspect that there are common features that span different languages and cultures, some characteristics of Arabic offensive language is language and culture specific. Thus, we conduct a thorough analysis of how Arabic users use offensive language. Next, we use the dataset to train strong Arabic offensive language classifiers using state-of-the-art representations and classification techniques. Specifically, we experiment with static and contextualized embeddings for representation along with a variety of classifiers such as a deep neural network classifier and Support Vector Machine (SVM).
The contributions of this paper are as follows:
We built the largest Arabic offensive language dataset to date that includes special tags for vulgar language and hate speech. We describe the methodology for building it along with annotation guidelines.
We performed thorough analysis of the dataset and described the peculiarities of Arabic offensive language.
We experimented with Support Vector Machine classifiers on character and word ngrams classification techniques to provide strong results on Arabic offensive language classification.
We built the largest Arabic offensive language dataset to date that includes special tags for vulgar language and hate speech.
Answer: Special tags for vulgar language and hate speech.
Question: What are some ways I could commute in to my office in downtown?
Answer: If you are located in a city you may have many commute options. You could use public transportation like a light rail or bus, ride your bike, or drive a car. If you have coworkers who live near you, you could consider carpooling.
Question: What are the prizes of the Festival of Festival in Saint Petersburg, Russia?
Evidence: Golden Gryphon, Silver Gryphon, Bronze Gryphon, The Nikolay Ovsyannikov Prize, Prize of the City of St. Petersburg, Prize of the Board, Prize for Talent and National Recognition
Answer: Grand Prix – Gold or Golden Gryphon (Griffon) - Awarded to the film rated highest by guests and participants

Silver Gryphon - Awarded to the film rated highest by audiences

Bronze Gryphon - Awarded to the best experimental film

The Nikolay Ovsyannikov Prize - Awarded for the best debut

Prize of the City of St. Petersburg - Awarded for contributions to world cinema made by a director whose film is featured in this year’s festival

Prize of the Board - Awarded to the screening section deemed to be this year’s best

Prize for Talent and National Recognition - Awarded to exceptional actors, actresses, and directors
Question: Write  the first paragraph of an advertising brochure describing an hotel nearby the Annecy Lake in France
Answer: This fantastic hotel is ideally located, minutes away from the Annecy Lake, one of the purest in Europe. The water temperature reaches 27 degrees celcius at the peak season, allowing the guests to swim and enjoy several water activities including wake surf and pedalo. Finally, this region is known for being the home of several cheese specialties like "Raclette" and "Tartiflette" to name a few.
Question: What classical machine learning algorithms are used?
Evidence: We ran three groups of experiments, to assess both the effectiveness of our approach when compared with the approaches we found in literature and its capability of extracting features that are relevant for sarcasm in a cross-domain scenario. In both cases, we denote with the word model one of the possible combinations of classic/statistical LSA and a classifier. The used classifiers are Support Vector Machine (SVM), Logistic regression (Log.Reg), Random Forest (RF) and gradient boosting (XGB).
The used classifiers are Support Vector Machine (SVM), Logistic regression (Log.Reg), Random Forest (RF) and gradient boosting (XGB).
Answer: The answers are shown as follows:
* Support Vector Machine (SVM)
* Logistic regression (Log.Reg)
* Random Forest (RF)
* gradient boosting (XGB)
Question: What is an actuary?
Answer: An actuary is a specialist in the valuation of the financial impact of risk and uncertainty. They apply statistical techniques and expert industry knowledge. Actuaries usually work in the insurance and banking industries.
Question: Classify the movies based on their genre.
The Pink Panther, Die Hard, No time to Die, Annabelle
Answer: Action - Die Hard, No time to Die
Horror - Annabelle
Comedy - The Pink Panther
Question: Which of the following are appropriate for a Black Tie dress code? A tuxedo, a blue suit, a loose sundress, a formal floor length gown?
Answer: A tuxedo and a formal floor length gown
Question: Give me a bullet point list of reasons to wear sunscreen
Answer: - To prevent sunburns
- To reduce the risk of skin cancer
- To lessen premature aging
- To protect your skin
Question: What are some common software pricing models?
Answer: There are many types of software pricing models, but broadly they can be divided into three categories: perpetual, subscription, and consumption.

Perpetual software pricing models, also known as perpetual licensing models, allow the software to be purchased for a one-time fee.  Typically the buyer has nearly unlimited use of the software in perpetuity.  If updates to the software are required, a separate software maintenance package may be purchased.

Subscription software allows unlimited use of the software for a predetermined period, often 1 year or 3 years, for a price.  Updates to the software are often included in the price of the subscription.  At the end of the subscription term, the buyer usually has the option to renew their subscription.

Consumption-based software allows the buyer to pay for their actual usage of the software during a period of time, for example monthly.  In this type of arrangement, the actual usage can vary from period to period, resulting in customer charges that vary as well.  Some customers like knowing that they will only pay for what they use, while other customers dislike the unpredictability of their bills.
Question: How do you prepare for case study interview for digital transformation case?
Answer: Here is one suggested approach. 1. Gather all requirements related to business problem 2. Understand data sources the business is using. 3. Understand if business would like to build or buy solutions 4. Check for industry specific accelerators 5. Start with one business unit and show the impact of digital transformation and then expand to other business units. 6. Do business value assessment like ROI 7. Focus on tangible and intangible benefits of digital transformation 8. Cost benefit analysis 9. Implementation plan and timelines 10. Production plan  11. Maintenance and support
Question: Identify which instrument is string or percussion: Davul, Begena
Answer: Begena is string, Davul is percission.
Question: What's the preferred mode of transportation in Vietnam?
Answer: You will often find the quickest, most enjoyable way to explore the cities of Vietnam is by motorbike. Whether it's a mo-ped, vespa, motorcycle, or dirt bike, these two wheeled options are the preferred method my many to get around.
Question: What benchmarks are created?
Evidence: In HotpotQA, on average we can find 6 candidate chains (2-hop) in a instance, and the human labeled true reasoning chain is unique. A predicted chain is correct if the chain only contains all supporting passages (exact match of passages).
In MedHop, on average we can find 30 candidate chains (3-hop). For each candidate chain our human annotators labeled whether it is correct or not, and the correct reasoning chain is not unique. A predicted chain is correct if it is one of the chains that human labeled as correct.
The accuracy is defined as the ratio:
In HotpotQA, on average we can find 6 candidate chains (2-hop) in a instance, and the human labeled true reasoning chain is unique. A predicted chain is correct if the chain only contains all supporting passages (exact match of passages).

In MedHop, on average we can find 30 candidate chains (3-hop). For each candidate chain our human annotators labeled whether it is correct or not, and the correct reasoning chain is not unique. A predicted chain is correct if it is one of the chains that human labeled as correct.

The accuracy is defined as the ratio:
The accuracy is defined as the ratio:
Answer: Answer with content missing: (formula) The accuracy is defined as the ratio # of correct chains predicted to # of evaluation samples
Question: What is the source of memes?
Evidence: We built a dataset for the task of hate speech detection in memes with 5,020 images that were weakly labeled into hate or non-hate memes, depending on their source. Hate memes were retrieved from Google Images with a downloading tool. We used the following queries to collect a total of 1,695 hate memes: racist meme (643 memes), jew meme (551 memes), and muslim meme (501 Memes). Non-hate memes were obtained from the Reddit Memes Dataset . We assumed that all memes in the dataset do not contain any hate message, as we considered that average Reddit memes do not belong to this class. A total of 3,325 non-hate memes were collected. We split the dataset into train (4266 memes) and validation (754 memes) subsets. The splits were random and the distribution of classes in the two subsets is the same. We didn't split the dataset into three subsets because of the small amount of data we had and decided to rely on the validation set metrics.
Hate memes were retrieved from Google Images with a downloading tool. We used the following queries to collect a total of 1,695 hate memes: racist meme (643 memes), jew meme (551 memes), and muslim meme (501 Memes). Non-hate memes were obtained from the Reddit Memes Dataset .
Answer: The answers are shown as follows:
* Google Images
* Reddit Memes Dataset
Question: Could any people access the corpus on GitHub2?
Evidence: As this corpus of annotated patient notes comprises original healthcare data which contains protected health information (PHI) per The Health Information Portability and Accountability Act of 1996 (HIPAA) BIBREF16 and can be joined to the MIMIC-III database, individuals who wish to access to the data must satisfy all requirements to access the data contained within MIMIC-III. To satisfy these conditions, an individual who wishes to access the database must take a “Data or Specimens Management” course, as well as sign a user agreement, as outlined on the MIMIC-III database webpage, where the latest version of this database will be hosted as “Annotated Clinical Texts from MIMIC” BIBREF17. This corpus can also be accessed on GitHub after completing all of the above requirements.
This corpus can also be accessed on GitHub2 after completing all of the above requirements.
Answer: No, they couldn't.
Question: Given this paragraph, what is the definition of Long short-term memory ?
Evidence: Long short-term memory (LSTM) is an artificial neural network used in the fields of artificial intelligence and deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. Such a recurrent neural network (RNN) can process not only single data points (such as images), but also entire sequences of data (such as speech or video). This characteristic makes LSTM networks ideal for processing and predicting data. For example, LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition, machine translation, speech activity detection, robot control, video games, and healthcare.
Answer: Long-short term memory is an artificial neural network used in deep learning that can process not only single data points (such as images), but also entire sequences of data (such as speech or video).
Question: Alice's parents have three daughters: Amy, Jessy, and what’s the name of the third daughter?
Answer: The name of the third daughter is Alice
Question: Why does Daenerys Targaryen want to rule Westeros?
Answer: According to the exiled Targaryen, she is steadfast in her belief that she is the rightful heir to the Iron Throne as she is the only living descendent of the last Targaryen monarch, her father, King Aerys II. Her father was murdered by his Kingsguard, Jaime Lannister, and his throne usurped by Robert Baratheon. Daenerys believes it is her birthright to reclaim the throne.
Question: According to this article, how many Scottish pounds would four Half-pistole be worth?
Evidence: A Half-pistole was a Scottish gold coin minted in 1701 under the reign of King William III. Along with the Pistole it was one of last gold coin minted for the Kingdom of Scotland before the Acts of Union 1707. The Half-pistole was equal to 6 Scottish pounds with an approximate value equal to the British Half guinea.
Answer: Four Half-pistole would be worth twenty-four (24) Scottish pounds. Each Half-pistole is 6 Scottish pounds and 6 x 4 = 24.
Question: Give this paragraph abount Battle of Adwa between Ethiopia and Italy, who were the commanders on Ethiopian side.
Evidence: Estimates for the Ethiopian forces under Menelik range from a low of 73,000 to a high of over 100,000 outnumbering the Italians by an estimated five times. The forces were divided among Emperor Menelik, Empress Taytu Betul, Ras Wale Betul, Ras Mengesha Atikem, Ras Mengesha Yohannes, Ras Alula Engida (Abba Nega), Ras Mikael of Wollo, Ras Makonnen Wolde Mikael,Fitawrari Habte Giyorgis, Fitawrari[nb 3] Gebeyyehu, and Negus[nb 4] Tekle Haymanot Tessemma. In addition, the armies were followed by a similar number of camp followers who supplied the army, as had been done for centuries. Most of the army consisted of riflemen, a significant percentage of whom were in Menelik's reserve; however, there were also a significant number of cavalry and infantry only armed with lances (those with lances were referred to as "lancer servants"). The Kuban Cossack army officer N. S. Leontiev who visited Ethiopia in 1895, according to some sources, led a small team of Russian advisers and volunteers. Other sources assert that Leontiev did not in fact participate in the battle, rather he visited Ethiopia first unofficially in January 1895, and then officially as a representative of Russia in August 1895, but then left later that year, returning only after the Battle of Adwa
Answer: Emperor Menelik, Empress Taytu, Ras Makonnen, Ras Wale Betul, Tekle Haymanot Tessemma, Ras Mengesha Yohannes, Ras Mikael were the top commanders and leaders.
Question: Why Interlaken is famous
Answer: Because of it's beautiful village. There are many wonderful scenic village adjacent to mountains and fountains.
Question: What are isobars and what are they commonly used for?
Evidence: An isobar is a line of equal or constant pressure on a graph, plot, or map; an isopleth or contour line of pressure. More accurately, isobars are lines drawn on a map joining places of equal average atmospheric pressure reduced to sea level for a specified period of time. In meteorology, the barometric pressures shown are reduced to sea level, not the surface pressures at the map locations. The distribution of isobars is closely related to the magnitude and direction of the wind field, and can be used to predict future weather patterns. Isobars are commonly used in television weather reporting.
Answer: An isobar is a line of equal or constant pressure on a graph, plot, or map. Isobars are commonly used in television weather reporting.
Question: What are the benefits of the author's method compared to other methods?
Evidence: Several studies have addressed the NMT-specific problem of missing or repeating words. Niehues2016 optimized NMT by adding the outputs of PBSMT to the input of NMT. Mi2016a and Feng2016 introduced a distributed version of coverage vector taken from PBSMT to consider which words have been already translated. All these methods, including ours, employ information of the source sentence to improve the quality of translation, but our method uses back-translation to ensure that there is no inconsistency. Unlike other methods, once learned, our method is identical to the conventional NMT model, so it does not need any additional parameters such as coverage vector or a PBSMT system for testing.
The attention mechanism proposed by Meng2016 considers not only the hidden states of the encoder but also the hidden states of the decoder so that over-translation can be relaxed. In addition, the attention mechanism proposed by Feng2016 computes a context vector by considering the previous context vector to prevent over-translation. These works indirectly reduce repeating and missing words, while we directly penalize translation mismatch by considering back-translation.
The encoder-decoder-reconstructor framework for NMT proposed by tu2016neural optimizes NMT by reconstructor using back-translation. They consider likelihood of both of forward translation and back-translation, and then this framework offers significant improvement in BLEU scores and alleviates the problem of repeating and missing words in the translation on a Chinese-English translation task.
All these methods, including ours, employ information of the source sentence to improve the quality of translation, but our method uses back-translation to ensure that there is no inconsistency. Unlike other methods, once learned, our method is identical to the conventional NMT model, so it does not need any additional parameters such as coverage vector or a PBSMT system for testing.
Answer: Unlike other methods, once learned, their method is identical to the conventional NMT model, so it does not need any additional parameters such as coverage vector or a PBSMT system for testing.
Question: Football or soccer?
Answer: Most of the world prefers to use the term "football". Exceptions include the United States of America, and to some extent, Australia, New Zealand, and even Ireland. These countries all play other sports called football, such as Gaelic football and American football, and so they use the term "soccer" to distinguish it from their other sport.
Question: What are some languages that feature hygienic macros?
Evidence: Hygienic macros are macros whose expansion is guaranteed not to cause the accidental capture of identifiers. They are a feature of programming languages such as Scheme, Dylan, Rust, Nim, and Julia. The general problem of accidental capture was well known within the Lisp community prior to the introduction of hygienic macros. Macro writers would use language features that would generate unique identifiers (e.g., gensym) or use obfuscated identifiers in order to avoid the problem. Hygienic macros are a programmatic solution to the capture problem that is integrated into the macro expander itself. The term "hygiene" was coined in Kohlbecker et al.'s 1986 paper that introduced hygienic macro expansion, inspired by the terminology used in mathematics.
Answer: Some languages that feature hygienic macros include Scheme, Dylan, Rust, Nim, and Julia.