inputs stringlengths 244 11.7k | targets stringlengths 12 173 | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringclasses 1
value | _template_type stringclasses 2
values |
|---|---|---|---|---|---|
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: We then proceed to connect these mentions i) if they co-occur within the same document (we will refer to th... | How does the differential privacy mechanism work?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries th... | What baselines other than standard transformers are used in experiments? | 6 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | Do they propose any further additions that could be made to improve generalisation to unseen speakers? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Each annotator annotated 90 reference sentences (i.e. from the training corpus) with which style they thought ... | Do they use dropout?
| 0 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What is the language model combination technique used in the paper? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: Our novelties include:
Using self-play learning for the neural response ranker (described in detail below)... | How is the political bias of different sources included in the model?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What is the benchmark dataset and is its quality high? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: How is segmentation quality evaluated? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example Input: To evaluate model robustness, we devise a test set consisting of ‘adversarial’ examples, i.e, p... | What unimodal detection models were used?
| 3 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: We consider two different models for each language pair: the Baseline and the Document model. We evaluate t... | How is their model different from BERT?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: Is SemCor3.0 reflective of English language data in general? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries th... | Are agglutinative languages used in the prediction of both prefixing and suffixing languages? | 6 | NIv2 | task461_qasper_question_generation | fs_opt |
instruction:
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
question:
This section reports the results of the experiments conducted on two data sets for evalu... | which languages are explored?
| 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
In this paper, we use three data sets from the literature to train and evaluate our own classifier. ... | What is dialogue act recognition?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: . We address various different challenges: dialogue act annotated data is not available for customer servic... | What are the tasks used in the mulit-task learning setup?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Let me give you an example: Questions are gathered from anonymized, aggregated queries to the Google search en... | What discourse relations does it work best/worst for? | 8 | NIv2 | task461_qasper_question_generation | fs_opt |
instruction:
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
question:
However, recent work has found that many NLI datasets contain biases, or annotation arti... | what is the size of BoolQ dataset?
| 9 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | What is the source of memes? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
Previous attempts to annotate QA-SRL initially involved trained annotators BIBREF4 but later resorte... | Are any of the utterances ungrammatical?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Input: Consider Input: Our novelties include:
Using self-play learning for the neural response ranker (descri... | Output: What network architecture do they use for SIM?
| 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: Our AV in-cabin data-set includes 30 hours of multimodal data collected from 30 passengers (15 female, 15 m... | How are weights dynamically adjusted?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | What is the WordNet counterpart for Persian? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | What previous automated evalution approaches authors mention? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What datasets did they use? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Let me give you an example: Questions are gathered from anonymized, aggregated queries to the Google search en... | On which tasks do they test their conflict method? | 8 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
We test our proposed approach for binary classification on either sarcasm or irony, on seven benchma... | What was the baseline?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example Input: We show that by determining and integrating heterogeneous set of features from different modali... | What datasets did they use?
| 3 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Input: Consider Input: The results in Table TABREF38 confirm the results of BIBREF13 and suggest that we succe... | Output: What previous automated evalution approaches authors mention?
| 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: What semi-supervised learning is applied? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Let me give you an example: Questions are gathered from anonymized, aggregated queries to the Google search en... | Which is more useful, visual or textual features? | 8 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: The overall Total Accuracy score reported in table TABREF19 using the entire feature set is 549.
A: Do th... | by how much did their model improve?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Let me give you an example: Questions are gathered from anonymized, aggregated queries to the Google search en... | What is the tagging scheme employed? | 8 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
More specifically, we observe the impact of: (i) pre-trained word embeddings BIBREF11, BIBREF12, rec... | What datasets do they use?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | What multilingual parallel data is used for training proposed model? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example Input: Bag-of-words feature vectors were used to train a multinomial logistic regression model. Let IN... | Do the authors mention any confounds to their study?
| 3 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | How does car speak pertains to a car's physical attributes? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
instruction:
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
question:
It is worth mentioning that the collected texts contain a large quantity of errors of se... | How big is the evaluated dataset?
| 9 | NIv2 | task461_qasper_question_generation | fs_opt |
TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: In this work, we analyze a set of tweets related to a specific classical music radio ... | Does the LRP method work in settings that contextualize the words with respect to one another?
| 8 | NIv2 | task461_qasper_question_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered fr... | Does the LRP method work in settings that contextualize the words with respect to one another? | 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What are the 18 propaganda techniques? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What embeddings are used? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
instruction:
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
question:
Then, it selects a subset of a 1,700-hour ( INLINEFORM2 1.1M instances) unlabeled datase... | What embeddings are used?
| 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | What insights into the relationship between demographics and mental health are provided? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: What is the size of this dataset? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
The baseline system for the SLC task is a very simple logistic regression classifier with default pa... | What is the size of this dataset?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries th... | After how many hops does accuracy decrease? | 6 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[Q]: Dataset Quality Analysis ::: Inter-Annotator Agreement (IAA)
To estimate dataset consistency across diffe... | Are the annotations automatic or manually created?
| 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example is below.
Q: Questions are gathered from anonymized, aggregated queries to the Google search engine... | Which models were compared? | 9 | NIv2 | task461_qasper_question_generation | fs_opt |
Part 1. Definition
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Part 2. Example
Questions are gathered from anonymized, aggregated queries to the Google sea... | What is a commonly used evaluation metric for language models? | 7 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: what datasets were used? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[Q]: We use two datasets in this work: the training is done on the Fisher Corpus English Part 1 (LDC2004S13) B... | What experiments do they use to quantify the extent of interpretability?
| 5 | NIv2 | task461_qasper_question_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no q... | What classification models were used? | 0 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[EX Q]: We conducted our experiments on the CMU ARCTIC database BIBREF33, which contains parallel recordings o... | What seven state-of-the-art methods are used for comparison?
| 6 | NIv2 | task461_qasper_question_generation | fs_opt |
Part 1. Definition
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Part 2. Example
Questions are gathered from anonymized, aggregated queries to the Google sea... | what are the baselines? | 7 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries th... | Is the model presented in the paper state of the art? | 6 | NIv2 | task461_qasper_question_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no q... | How many CNNs and LSTMs were ensembled? | 0 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
As the gold standard sentiment lexica, we chose manually created lexicon in Czech BIBREF11 , German ... | Which publicly available NLU dataset is used?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example Input: Hausa language is the second most spoken indigenous language in Africa with over 40 million nat... | Is the model presented in the paper state of the art?
| 3 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
We aim to find such content in the social media focusing on the tweets.
Ex Output:
Does the dataset... | What is the challenge for other language except English
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered fr... | What is the challenge for other language except English | 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
--------
Question: For the task-oriented system, although there are some objective evaluation metrics, such as ... | What were the variables in the ablation study?
| 7 | NIv2 | task461_qasper_question_generation | fs_opt |
Detailed Instructions: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
See one example below:
Problem: Questions are gathered from anonymized, aggregated queri... | what is their explanation for the effectiveness of back-translation? | 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[Q]: The final embedding dimensionality is equal to the number of unique word labels in the training set, whic... | How do they correlate user backstory queries to user satisfaction?
| 5 | NIv2 | task461_qasper_question_generation | fs_opt |
instruction:
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
question:
We evaluate our model in a simulated binning task in which the robot is tasked to place ... | what is their explanation for the effectiveness of back-translation?
| 9 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Let me give you an example: Questions are gathered from anonymized, aggregated queries to the Google search en... | Overall, does having parallel data improve semantic role induction across multiple languages? | 8 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that a... | Solution: Does API provide ability to connect to models written in some other deep learning framework? | 5 | NIv2 | task461_qasper_question_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no q... | How big is the provided treebank? | 0 | NIv2 | task461_qasper_question_generation | fs_opt |
TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: To study how the multimodal context can boost the performance compared to an unimodal... | How big is the provided treebank?
| 8 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | What models are evaluated with QAGS? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered fr... | How are resources adapted to properties of Chinese text? | 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
Fenerbahçe We have decided to consider tweets about popular sports clubs as our domain for stance de... | How do they combine audio and text sequences in their RNN?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
One example: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries th... | What classical machine learning algorithms are used? | 6 | NIv2 | task461_qasper_question_generation | fs_opt |
TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: We perform our experiments using ActivityNet Captions dataset BIBREF2 that is conside... | Is there any example where geometric property is visible for context similarity between words?
| 8 | NIv2 | task461_qasper_question_generation | fs_opt |
Part 1. Definition
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Part 2. Example
Questions are gathered from anonymized, aggregated queries to the Google sea... | How large is the dataset? | 7 | NIv2 | task461_qasper_question_generation | fs_opt |
Part 1. Definition
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Part 2. Example
Questions are gathered from anonymized, aggregated queries to the Google sea... | Can named entities in SnapCaptions be discontigious? | 7 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: We conduct various experiments to illustrate the properties that are encouraged via different KL magnitudes... | How did they get relations between mentions?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
Teacher: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Questions ... | what corpus is used to learn behavior? | 2 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Input: Consider Input: The resulting set of 46 documents makes up our base corpus. Note that these documents v... | Output: what corpus is used to learn behavior?
| 2 | NIv2 | task461_qasper_question_generation | fs_opt |
Detailed Instructions: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
See one example below:
Problem: Questions are gathered from anonymized, aggregated queri... | Does the dataset they use differ from the one used by Pasupat and Liang, 2015? | 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: In our experiments, we use as input the 2210 tokenized sentences of the Stanford Sentiment Treebank test se... | What are results of comparison between novel method to other approaches for creating compositional generalization benchmarks?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
--------
Question: We first run our experiment on BiLSTM, BiLSTM-CNN, BiLSTM-CRF BiLSTM-CNN-CRF using the hyper... | What is the size of the dataset?
| 7 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[EX Q]: A baseline model for automatic extraction of anglicisms was created using the annotated corpus we just... | How they evaluate quality of generated output?
| 6 | NIv2 | task461_qasper_question_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example: Questions are gathered fr... | Which machine baselines are used? | 1 | NIv2 | task461_qasper_question_generation | fs_opt |
TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: On the other hand, Go-Explore Seq2Seq shows promising results by solving almost half ... | Which pre-trained transformer do they use?
| 8 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Example input: Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries... | What datasets used for evaluation? | 3 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
[EX Q]: In contrast to existing bottlenecks, this work targets three different types of social networks (Forms... | Which machine baselines are used?
| 6 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Q: E2E NLG challenge Dataset: The training set of the E2E challenge dataset which consists of 42K samples was ... | What datasets used for evaluation?
****
| 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
As mentioned in subsec:datasets, all the word-similarity datasets contain pairs of words annotated w... | How they know what are content words?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
Detailed Instructions: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
See one example below:
Problem: Questions are gathered from anonymized, aggregated queri... | what ml based approaches were compared? | 4 | NIv2 | task461_qasper_question_generation | fs_opt |
In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Ex Input:
To evaluate the influence of our hypersphere feature for off-the-shelf NER systems, we perform the N... | What are the benchmark models?
| 1 | NIv2 | task461_qasper_question_generation | fs_opt |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 3