# Detecting Everyday Scenarios in Narrative Texts

## TL;DR

This paper introduces the task of scenario detection in narrative texts, aiming to identify references to 200 different everyday activity scripts, and provides a benchmark dataset and baseline model for this task.

## Contribution

It presents the first benchmark dataset and baseline model for scenario detection, covering a wide range of scripts in narrative texts.

## Key findings

- Developed a new benchmark dataset for scenario detection
- Proposed a baseline model using topic segmentation and text classification
- Demonstrated the feasibility of identifying script references in narratives

## Abstract

Script knowledge consists of detailed information on everyday activities. Such information is often taken for granted in text and needs to be inferred by readers. Therefore, script knowledge is a central component to language comprehension. Previous work on representing scripts is mostly based on extensive manual work or limited to scenarios that can be found with sufficient redundancy in large corpora. We introduce the task of scenario detection, in which we identify references to scripts. In this task, we address a wide range of different scripts (200 scenarios) and we attempt to identify all references to them in a collection of narrative texts. We present a first benchmark data set and a baseline model that tackles scenario detection using techniques from topic segmentation and text classification.