DataHammer/scimrc huggingface dataset:
Question: what metrics are used in evaluation?
Evidence: We evaluate our approach on two well benchmarked sequence tagging tasks, the CoNLL 2003 NER task BIBREF13 and the CoNLL 2000 Chunking task BIBREF14 . We report the official evaluation metric (micro-averaged INLINEFORM0 ). In both cases, we use the BIOES labeling scheme for the output tags, following previous work which showed it outperforms other options BIBREF15 . Following BIBREF8 , we use the Senna word embeddings BIBREF2 and pre-processed the text by lowercasing all tokens and replacing all digits with 0.
FLOAT SELECTED: Table 1: Test set F1 comparison on CoNLL 2003 NER task, using only CoNLL 2003 data and unlabeled text.
We report the official evaluation metric (micro-averaged INLINEFORM0 ). 
FLOAT SELECTED: Table 1: Test set F1 comparison on CoNLL 2003 NER task, using only CoNLL 2003 data and unlabeled text.
Answer: micro-averaged F1
Question: Do they survey visual question generation work?
Evidence: Visual Question Generation (VQG) is another emerging topic which aims to ask questions given an image. We categorize VQG into grounded- and open-ended VQG by the level of cognition. Grounded VQG generates visually grounded questions, i.e., all relevant information for the answer can be found in the input image BIBREF74 . A key purpose of grounded VQG is to support the dataset construction for VQA. To ensure the questions are grounded, existing systems rely on image captions to varying degrees. BIBREF75 and BIBREF76 simply convert image captions into questions using rule-based methods with textual patterns. BIBREF74 proposed a neural model that can generate questions with diverse types for a single image, using separate networks to construct dense image captions and to select question types.
In contrast to grounded QG, humans ask higher cognitive level questions about what can be inferred rather than what can be seen from an image. Motivated by this, BIBREF10 proposed open-ended VQG that aims to generate natural and engaging questions about an image. These are deep questions that require high cognition such as analyzing and creation. With significant progress in deep generative models, marked by variational auto-encoders (VAEs) and GANs, such models are also used in open-ended VQG to bring “creativity” into generated questions BIBREF77 , BIBREF78 , showing promising results. This also brings hope to address deep QG from text, as applied in NLG: e.g., SeqGAN BIBREF79 and LeakGAN BIBREF80 .
Visual Question Generation (VQG) is another emerging topic which aims to ask questions given an image.
Motivated by this, BIBREF10 proposed open-ended VQG that aims to generate natural and engaging questions about an image.
Answer: Yes.
Question: What's the oldest capital in the world?
Evidence: Damascus (/dəˈmæskəs/ də-MASS-kəs, UK also /dəˈmɑːskəs/ də-MAH-skəs; Arabic: دمشق‎, romanized: Dimashq, IPA: [diˈmaʃq]) is the capital of Syria, the oldest capital in the world and, according to some, the fourth holiest city in Islam. Known colloquially in Syria as aš-Šām (الشَّام‎) and dubbed, poetically, the "City of Jasmine" (مَدِينَةُ الْيَاسْمِينِ‎ Madīnat al-Yāsmīn), Damascus is a major cultural center of the Levant and the Arab world.
Answer: Damascus
Question: Give me a list of the best animals one can have for a pet, starting with the best pet first.
Answer: 1. Cat
2. Dog
3. Rabbit
4. Bird
5. Fish
6. Snake
7. Hamster
8. Gerbil
9. Guinea pig
10. Chinchilla
Question: What is the appeal to baby led weaning?
Answer: Baby led weaning, or BLW, is the practice of weaning a baby from breast feeding naturally by allowing the child to begin eating solid food freely by their own choice. For example, while the care takers are eating a meal, allowing the child (at any age) to pick food from the care taker's plate. There is the thought is that the human body will self regulate what it needs instinctively.   The notion of self regulation applies to nutrients found in the food as well as the amount of food that the body need.  The mainstream alternative (especially in first world countries) is pureed foods prepared especially for babies. Those that subscribe to BLW believe that the downside of feeding babies baby specific food is that the practice teaches babies to ignore natural instincts because someone else is in control of what type and how much food to eat.  Some reasons people choose not to follow BLW are: the misconception that babies cannot eat solid food,  the convenience of prepared commercial baby food, generally accepted mainstream guidance on baby rearing, or the lack of awareness of BLW. BLW can also be quite messy as some of the food babies will handle are a function of exploration rather than for consumption and therefore end up on the floor.
Question: Chronological order of the Alien movie universe
Answer: 1. Alien vs. Predator
2. Aliens vs. Predator: Requiem
3. Prometheus
4. Alien: Covenant
5. Alien
6. Aliens
7. Alien 3
8. Alien: Resurrection
Question: How much did Shaffer donate?
Evidence: In 2018, Butler County Community College created The Shaffer School of Nursing and Allied Health after Shaffer donated $1 million to the school.
Answer: $1 million
Question: Who were the original members of the Pivit band, and how many albums did they record?
Evidence: Pivit is an American punk rock band hailing from Poway and Cardiff, California, formed in late 1994 by original drummer Mark McLemore, lead singer Chris Moore, and guitarist Eric Sisson in San Diego County, California. In 1995, they recorded their first demo entitled Find the Fuzz. Eventually they produced 3 albums together, Pressure in 1996, Millennium in 1998 and finally Thanks for Coming Back in 2002.
Answer: The original members were Mark McLemore on drums, lead singer Chris Moore, and guitarist Eric Sisson. They produced 3 albums together.
Question: Given this paragraph, how many seasons are there of Ted Lasso?
Evidence: The first season of ten episodes premiered on Apple TV+ on August 14, 2020, with three episodes followed by weekly installments. A second season of 12 episodes premiered on July 23, 2021. In October 2020, the series was renewed for a third season, which premiered on March 15, 2023.
Answer: As of March 2023, there have been 3 seasons of Ted Lasso.
Question: What are the main reasons Parisians want electric scooters to be banned according to the following article?
 
Parisians are voting on Sunday on whether to rid the streets of the French capital of electric scooters, although some say the city’s leaders ought to be focusing on more pressing issues.

Paris was a pioneer when it introduced e-scooters, or trottinettes, in 2018 as the city’s authorities sought to promote non-polluting forms of urban transport.

But as the two-wheeled vehicles grew in popularity, especially among young people, so did the number of accidents: in 2022, three people died and 459 were injured in e-scooter accidents in Paris.

In what is being billed as a “public consultation” voters are being asked: “For or against self-service scooters?”

Twenty-one polling stations have been set up across the city and will be open until 7pm local time, with the result expected at around 10pm.

Electric scooters available for rent on the Place du Trocadero, Paris.
E-scooters: a tale of two cities as London and Paris plot different paths
Read more
Although 1.6 million people are eligible to vote, turnout is expected to be low.

Paris’s socialist mayor, Anne Hidalgo, has promoted cycling and bike-sharing but supports a ban on e-scooters.

In an interview with Agence France-Presses last week, Hidalgo said “self-service scooters are the source of tension and worry” for Parisians and that a ban would “reduce nuisance” in public spaces. However, she promised to respect the outcome of the vote even if it is not legally binding.

Paris has almost 15,000 e-scooters across its streets, operated by companies including Lime, Dott and Tier.

Detractors argue that e-scooter users disrespect the rules of the road and regularly flout a ban on riding on pavements. The vehicles are also often haphazardly parked or thrown into the River Seine.

In June 2021, a 31-year-old Italian woman was killed after being hit by an e-scooter with two passengers onboard while walking along the Seine.

“Scooters have become my biggest enemy. I’m scared of them,” Suzon Lambert, a 50-year-old teacher from Paris, told AFP. “Paris has become a sort of anarchy. There’s no space any more for pedestrians.”

Another Parisian told BFMTV: “It’s dangerous, and people use them badly. I’m fed up.”

Julian Sezgin, aged 15, said he often saw groups of two or three teenagers on e-scooters zooming past cars on busy roads. “I avoid going on e-scooters and prefer e-bikes as, in my opinion, they are safer and more efficient,” he told the Guardian.
Answer: According to the Mayor of Paris, Parisians want to ban e-scooters because they are a source of tension and worry and banning them would reduce nuisance in public spaces. 
Detractors of e-scooters think that their users disrespect the rules of the road and park them haphazardly, causing anarchy in the streets and making the life of pedestrians difficult and dangerous.
Question: What is the meaning of inference in this paper?
Evidence: Reasoning is part of our every day routine: we hear Natural Language (NL) sentences, we participate in dialogues, we read books or legal documents. Successfully understanding, participating or communicating with others in these situations presupposes some form of reasoning: about individual sentences, whole paragraphs of legal documents, small or bigger pieces of dialogue and so on. The human reasoning performed in these different situations cannot be explained by a single rigid system of reasoning, plainly because reasoning is performed in different ways in each one of them. Consider the following example:
Three representatives are needed.
If a human reasoner with expert knowledge was to interpret the above utterance in a legal context, s/he will most probably judge that a situation where more than three references are provided could be compatible with the semantics of the utterance. To the contrary, if the same reasoner was to interpret the above as part of a casual, everyday conversation, then three would most likely be interpreted as exactly three, making the same situation incompatible with the utterance. In this paper, we want to focus on precise inference, inference which is either performed by experts or normal people after taking some time to consider the inferences that follow or not from a set of premises. The problem one encounters in testing systems of this type of reasoning is the fact that no large scale datasets of this sort of inference exist. The commonly used datasets for systems fit for this type of precise reasoning, i.e. logical systems based on some model of formal semantics for Natural Language (NL), are the FraCaS test suite and the Recognizing Textual Entailment (RTE) datasets.
In this paper, we want to focus on precise inference, inference which is either performed by experts or normal people after taking some time to consider the inferences that follow or not from a set of premises.
Answer: The inference is either performed by experts or normal people after taking some time to consider the inferences that follow or not from a set of premises.
Question: Which players won the men's singles grand slam tennis tournaments in 2022.
Answer: The following players won the men's singles grand slam tennis tournaments in 2022:
- Rafael Nadal won the Australian Open and the French Open
- Novak Djokovic won Wimbledon
- Carlos Alcaraz won the US Open
Question: Kindly provide some details regarding the plot of science fiction 'A Borrowed Man' from the given passage.
Evidence: In the 22nd century, Ern A. Smithe is a "reclone" of a mystery writer, embedded with the recorded memories of his original and stored in a library where patrons can consult or borrow him. He is checked out by a woman who hopes that he can help solve the deaths of her father and brother, because her father's safe had contained nothing except one of Smithe's novels. However, Smithe's original was not a detective, only someone who wrote about them — and his knowledge of the world is over a century out of date.
Answer: 1. In the 22nd century, Ern A. Smithe is a "reclone" of a mystery writer, embedded with the recorded memories of his original and stored in a library where patrons can consult or borrow him.
2. He is checked out by a woman who hopes that he can help solve the deaths of her father and brother, because her father's safe had contained nothing except one of Smithe's novels.
3.  However, Smithe's original was not a detective, only someone who wrote about them — and his knowledge of the world is over a century out of date.
Question: Which word is different from the rest: cap, turban, veil, hat
Answer: All except veil covers the head, while veil covers the face
Question: Who is Taehoon Oh?
Answer: Taehoon Oh is a computer graphic specialist, game designer and developer. He is a co-founder and COO at Studio Roqovan, formerly known as Reload Studios. He was a lead artist and was one of the pioneer developers of the Call of Duty game franchise. He is also one of the co-founders of the non-gaming virtual reality subdivision of Studio Roqovan called Rascali, launched in September 2015
Question: What did the operators do when carrying out text annotation?
Evidence: Clinical researchers teamed with junior medical residents in collaboration with more senior intensive care physicians to carry out text annotation over the period of one year BIBREF13. Operators were grouped to facilitate the annotation of notes in duplicate, allowing for cases of disagreement between operators. The operators within each team were instructed to work independently on note annotation. Clinical texts were annotated in batches which were time-stamped on their day of creation, when both operators in a team completed annotation of a batch, a new batch was created and transferred to them.
Two groups (group 1: co-authors ETM & JTW; group 2: co-authors JW & JF) of two operator pairs of one clinical researcher and one resident physician (who had previously taken the MCAT®) first annotated nursing notes and then discharge summaries. Everyone was first trained on the high-context phenotypes to look for as well as their definitions by going through a number of notes in a group. A total of 13 phenotypes were considered for annotation, and the label “unsure” was used to indicate that an operator would like to seek assistance determining the presence of an phenotype from a more senior physician. Annotations for phenotypes required explicit text in the note indicating the phenotype, but as a result of the complexity of certain phenotypes there was no specific dictionary of terms, or order in which the terms appeared, required for a phenotype to be considered present.
Two groups (group 1: co-authors ETM & JTW; group 2: co-authors JW & JF) of two operator pairs of one clinical researcher and one resident physician (who had previously taken the MCAT R ) first annotated nursing notes and then discharge summaries.
Answer: They first annotated nursing notes and then discharge summaries.
Question: Which animal is the most faster?
Answer: The fastest animal on land is the cheetah (Acinonyx jubatus), capable of reaching speeds of up to 70 miles per hour (112 kilometers per hour) over short distances. They achieve these impressive speeds through their slender build, flexible spine, and long legs, which allow them to take long strides and cover a lot of ground with each stride.

However, if we consider all animals, including those that fly or swim, the peregrine falcon (Falco peregrinus) is the fastest animal in the world. It can reach speeds of up to 240 miles per hour (386 kilometers per hour) during a hunting dive known as a stoop, making it the fastest animal in the world overall.

It's worth noting that different animals have different ways of measuring their speed, and some species are faster in certain situations than in others. However, in terms of pure top speed, the cheetah and peregrine falcon are among the fastest animals on the planet.
Question: From the passage identify the spin-off games release in the universe of Clash of Clans. Display the results in a comma separated format.
Evidence: Clash of Clans is a 2012 free-to-play mobile strategy video game developed and published by Finnish game developer Supercell. The game was released for iOS platforms on August 2, 2012, and on Google Play for Android on October 7, 2013.

The game is set in a fantasy-themed persistent world where the player is a chief of a village. Clash of Clans tasks players to build their own village using the resources gained from attacking other player's villages with troops; earning rewards, buying them with medals or by producing them at their own village. The main resources are gold, elixir and dark elixir. Players can conjoin to create clans, groups of up to fifty people, who can then participate in Clan Wars together, donate and receive troops, and chat with each other. The minimum number of players of a Clan War is thirty. 

Clash of Clans was released to generally positive reviews from critics.

Four spin-off games in the same universe of Clash of Clans were developed by Supercell. The first, Clash Royale, was released in 2016. The other three, Clash Quest, Clash Mini, and Clash Heroes, were announced in April 2021. Clash Quest development was discontinued on 17 August 2022.[9
Answer: Clash Royale, Clash Quest, Clash Mini, Clash Heroes
Question: What off-the-shelf QA model was used to answer sub-questions?
Evidence: We find that our approach is robust to the single-hop QA model that answers sub-questions. We use the $\textsc {BERT}_{\textsc {BASE}}$ ensemble from BIBREF3 as the single-hop QA model. The model performs much worse compared to our $\textsc {RoBERTa}_{\textsc {LARGE}}$ single-hop ensemble when used directly on HotpotQA (56.3 vs. 66.7 F1). However, the model results in comparable QA when used to answer single-hop sub-questions within our larger system (79.9 vs. 80.1 F1 for our $\textsc {RoBERTa}_{\textsc {LARGE}}$ ensemble).
 We use the $\textsc {BERT}_{\textsc {BASE}}$ ensemble from BIBREF3 as the single-hop QA model. 
Answer: The answers are shown as follows:
* $\textsc {BERT}_{\textsc {BASE}}$ ensemble from BIBREF3
Question: In the series A Song of Ice and Fire, who is the founder of House Oakheart?
Answer: John the Oak
Question: What is a hurricane?
Answer: A hurricane is a form of a tropical cyclone.  They usually start in the middle of the ocean near the equator in warm waters and develop in size to thousands of miles wide.  They have a low pressure center, are spiral in nature, and are characterized by high winds.  They are very destructive due to their high winds, torrential rain, and storm surge when they approach land.
Question: What is a verb?
Answer: A verb is an action word that describes an activity.  Examples of verbs are the following: swimming, hiking, biking, roller skating, or skydiving.  All of these single and combination word examples are tied to an activity that any living thing can do.  For example, a dog can bike ride with a human when the human is pedaling the bike.  Verb use is not limited to humans or people only but applies to all living things.
Question: What's the difference between Spiders and insects?
Answer: Even though both spiders and insects are exoskeletons, Spiders are not insects. Spiders have eight legs, and all insects have six legs.
Question: Which medical tool was developed by Sanctorius in 1612
Answer: Thermometer
Question: What is the architecture of the framework？
Evidence: Our framework consists of a question answering model and a question generation model.
We implement two question answering models, which directly measure the semantic similarity between questions and candidate answers in the semantic space. First, to make the model's prediction more explainable, we implement a path based QA model PCNet. In this model, to get candidate answers from the triplets based document for a given question. We first retrieve the an “anchor” point $arg1_i$ or $arg2_i$ in the document fact $f_i$ . These anchors are selected based on edit distance between the words in the questions and the arguments. Then we regard all arguments in the 1-hops and 2-hops fact of the anchors as answers. However, the coverage of the candidate answers can be 100% in the model. We then implement a second end-to-end neural model KVMenNet which covers all the answers but with less interpretability. Both models generate a score $f_{qa}(q, a)$ of each candidate answer.
We then implement a generation-based model. The motivation to design this model is that we want to associate natural language phrases with knowledge based representation. It takes semantics of a candidate answer as the input and generates a question $\hat{q}$ . Then a paraphrasing model gives a score $f_{qg}(q,\hat{q})$ , which is computed between the generated question $\hat{q}$ and the original question $q$ , as the ranking score.
We get the final scores $S(q,a)$ used for ranking as follows. 
$$S(q,a) = \lambda f_{qa}(q, a) + (1-\lambda ) f_{qg}(q,\hat{q})$$   (Eq. 7) 
Moreover, we incorporate side information from external KBs into the three models. The details of how we use external KBs to enhance the representation of elements in the document KB will be described in section Incorporating External Knowledge.
Our framework consists of a question answering model and a question generation model.
Answer: Their framework consists of a question answering model and a question generation model.
Question: What are the three types of platforms to support the development of conversational systems?
Evidence: Regarding current platforms to support the development of conversational systems, we can categorize them into three types: platforms for plugging chatbots, for creating chatbots and for creating service chatbots. The platforms for plugging chatbots provide tools for integrating them another system, like Slack. The chatbots need to receive and send messages in a specific way, which depends on the API and there is no support for actually helping on building chatbots behavior with natural language understanding. The platforms for creating chatbots mainly provide tools for adding and training intentions together with dialogue flow specification and some entities extraction, with no reasoning support. Once the models are trained and the dialogue flow specified, the chatbots are able to reply to the received intention. The platforms for creating service chatbots provide the same functionalities as the last one and also provide support for defining actions to be executed by the chatbots when they are answering to an utterance. Table TABREF43 summarizes current platforms on the market accordingly to these categories. There is a lack on platforms that allow to create chatbots that can be coordinated in a multiparty chat with governance or mediation.
Regarding current platforms to support the development of conversational systems, we can categorize them into three types: platforms for plugging chatbots, for creating chatbots and for creating service chatbots.
Answer: The platforms for plugging chatbots, for creating chatbots and for creating service chatbots.