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 obtained 9,892 stories of sexual harassment incidents that was reported on Safecity. Those stories include a text description, along with tags of the forms of harassment, e.g. commenting, ogling and groping. A dataset of these stories was published by Karlekar and Bansal karlekar2018safecity. In addition to the forms of harassment, we manually annotated each story with the key elements (i.e. “harasser", “time", “location", “trigger"), because they are essential to uncover the harassment patterns. An example is shown in Figure FIGREF3. Furthermore, we also assigned each story classification labels in five dimensions (Table TABREF4). The detailed definitions of classifications in all dimensions are explained below.

A: What is the size of the dataset?
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Q: We compare FSDM with four baseline methods and two ablations.

NDM BIBREF7 proposes a modular end-to-end trainable network. It applies de-lexicalization on user utterances and responses.

LIDM BIBREF9 improves over NDM by employing a discrete latent variable to learn underlying dialogue acts. This allows the system to be refined by reinforcement learning.

KVRN BIBREF13 adopts a copy-augmented Seq2Seq model for agent response generation and uses an attention mechanism on the KB. It does not perform belief state tracking.

TSCP/RL BIBREF10 is a two-stage CopyNet which consists of one encoder and two copy-mechanism-augmented decoders for belief state and response generation.

A: What baselines have been used in this work?
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Q: Results on all sets show an important difference between precision and recall, precision being significantly higher than recall. There is also a significant difference between the results obtained on development and test set (F1 = 89.60, F1 = 87.82) and the results on the supplemental test set (F1 = 71.49). The time difference between the supplemental test set and the development and test set (the headlines from the the supplemental test set being from a different time period to the training set) can probably explain these differences.

A:
What is the performance of the CRF model on the task described?
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