Lotte and Annette: A Framework for Finding and Exploring Key Passages in Literary Works (2021)

Abstract: We present an approach that leverages expert knowledge contained in scholarly works to automatically identify key passages in literary works. Specifically, we extend a text reuse detection method for finding quotations, such that our system Lotte can deal with common properties of quotations, for example, ellipses or inaccurate quotations. An evaluation shows that Lotte outperforms four existing approaches. To generate key passages, we combine overlapping quotations from multiple scholarly texts. An interactive website, called Annette, for visualizing and exploring key passages makes the results accessible and explorable.

## introduction identification of key passages in nonfiction has long been a topic of research. for example, in the context of text summarization to identify sentences and passages which contain key arguments @xcite . while there has been a lot of progress for nonfiction @xcite , there are no working solutions for fiction. in this paper, we present a first step towards a system to automatically identify key passages in fiction. we understand key passages as passages that are particularly important to expert readers, following a general definition of "key words" @xcite . we leverage the expert knowledge contained in scholarly works to automatically identify potential key passages. authors of scholarly works use different types of citations to refer to original works, for example, quotations or paraphrases. we adapt existing methods for text re-use detection @xcite ) such that our system can deal with common properties of quotations such as ellipses or unclean quotations, for instance, missing words or spelling mistakes. on top of that, our system works independently of the order of quotations and can handle multiple quotations of the same text. to generate key passages, we combine overlapping quotations from multiple scholarly works. our contributions are lotte, an algorithm and python tool for quotation detection in fictional texts and annette, an interactive website for visualizing and exploring key passages. this makes key passages available at a larger scale and in structured form and opens up many new opportunities for analyses in literary studies and the praxeology of literary studies. this paper is organized as follows: in section 2, we provide an overview on related work. in section 3, we present our approach to finding key passages. in section 4, we describe our evaluation setup including four existing systems and in section 5 we show how our approach outperforms them. finally, in section 6, we present our tool for visualizing and exploring key passages. ## related work quotation detection can be regarded as a kind of text reuse detection, which is frequently applied for plagiarism detection @xcite . there, the goal is to find quotations and citations without proper attribution. in our case, we assume proper attribution and focus on the step of finding and linking quotations. several tools for different use cases try to solve similar or related problems. for example, blast aligns biological sequences @xcite and has been adopted for text reuse detection @xcite . copyfind @xcite is an open source tool for comparing documents written in c++. while passim @xcite and textmatcher @xcite are simple text reuse detection tools, tracer @xcite is an elaborate framework consisting of around 700 algorithms. sim @xcite ) finds lexical similarities in source code and natural language texts, originally built to find duplicate code in large code bases. the original idea worked well enough to be used to find copied work in student submissions. sim works with a number of programming languages and can easily be extended to work with new languages by providing a lexical description. sim_text is a version of sim for checking duplicates in natural language texts. based on sim, similarity texter (simt) is a tool for text comparison written in javascript by @xcite . for various reasons, these tools are not appropriate for detecting key passages. for example, textmatcher only finds quotations that appear in the same order in both texts. none of the tools can find multiple quotations of the same text. in section 5 we evaluate blast, copyfind, simt, and textmatcher and compare them against our approach. we did not evaluate tracer, as we could not manage to extract exact matches. passim is the only system we could not get to work at all as its dependencies were no longer available. a website for visualizing (literal) citations of shakespeare's works has been presented by miller. it visualizes how often each line from every play has been cited in jstor's journal collection. the website is limited to the visualization of the citation frequency of each line and does not offer any functionality to explore the source of citations. ## lotte -a text reuse detection tool in this section, we describe our approach for identifying quotations which solves the following task: 1 given a source and a target text, it finds all instances where the target text contains some part of the source text. our approach is based on a modified and extended version of sim_text by @xcite . the original implementation is written in c while our reimplementation is in python. reimplementing the algorithm allowed us to integrate extensions for properly handling specific properties of quotations which are not covered by sim_text. the algorithm works in five main steps which we describe in the sequel. ## visualizing and exploring key passages here, we describe how the results of lotte are integrated into an interactive website for visualizing and exploring key passages. foot_1 ## conclusion we presented an approach for finding and visualizing key passages in literary works using scholarly works. for finding the quotations, we developed a system called lotte by adapting sim_text @xcite . our approach outperforms prior approaches for text reuse detection. the matches are further processed to identify key passages by combining overlapping matches. we also presented annette, a website that visualizes the literary work and scholarly articles together with the found quotations and thus allows us to explore the identified key passages and their origin. the current system only considers matches of length five and greater. in the future, we want to also identify shorter quotations and investigate how much information these add compared to longer ones. another limitation of the current system is the missing suppport for handling ambiguous quotations. we have shown that this becomes more relevant the longer the source texts are. one solution to resolve such cases could be to utilize page references about the quoted passage, which are often included in the scholarly text. furthermore, we aim to identify and analyze paraphrases and renarrations of literary works.