In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

In addition to the majority baseline, we also compare our results with a lexicon-based approach. For experimental results, we report majority baseline for each language where the majority baseline corresponds to a model's accuracy if it always predicts the majority class in the dataset.
Question: what are the baselines?
majority baseline lexicon-based approach

For English dataset, we crawl 687 cybersecurity articles from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018.
Question: Where are the cybersecurity articles used in the model sourced from?
from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018

We conduct our annotation study on Amazon Mechanical Turk, presenting Turkers with Human Intelligence Tasks (henceforth, HITs) consisting of a single conversation between a customer and an agent. In each HIT, we present Turkers with a definition of each dialogue act, as well as a sample annotated dialogue for reference. For each turn in the conversation, we allow Turkers to select as many labels from our taxonomy as required to fully characterize the intent of the turn. Additionally, annotators are asked three questions at the end of each conversation HIT, to which they could respond that they agreed, disagreed, or could not tell:
Question: How are customer satisfaction, customer frustration and overall problem resolution data collected?
By annotators on Amazon Mechanical Turk.