Simplifying metaphorical language for young readers: A corpus study on news text

Abstract

The paper presents first results of an ongoing project on text simplification focusing on linguistic metaphors. Based on an analysis of a parallel corpus of news text professionally simplified for different grade levels, we identify six types of simplification choices falling into two broad categories: preserving metaphors or dropping them. An annotation study on almost 300 source sentences with metaphors (grade level 12) and their simplified counterparts (grade 4) is conducted. The results show that most metaphors are preserved and when they are dropped, the semantic content tends to be preserved rather than dropped, however, it is reworded without metaphorical language. In general, some of the expected tendencies in complexity reduction, measured with psycholinguistic variables linked to metaphor comprehension, are observed, suggesting good prospect for machine learning-based metaphor simplification. Motivation and problem statementText simplification is the process of meaning preserving reduction of discourse complexity whose purpose is to adapt text for specific populations of readers, for instance, children or language learners. The idea has been around since "My Weekly Reader" in the 1920s and Palmer's work (1932) and over the past 20 years has attracted attention of the computational linguistics community. While broadly interpreted "lexical simplification" -in general understood as substitution of "difficult" words with "simpler" ones -is a common component of automated simplification systems (see, for instance, (Siddharthan, 2014)), studies of text simplification dedicated to specific lexis-related semantic phenomena are lacking. One class of such understudied phenomena are those related to figurative language; a surprising gap in the simplification research considering that metaphors have been shown to cause difficulties in text comprehension and that developing metaphor interpretation competence is a complex developmental process (for an overview, see, for instance, (Winner, 1997)). Since automated systems are trained on corpora of simplified text, understanding patterns of metaphor simplification based on corpus data could help improve simplification models.In this paper we present a study that is our first step in this direction.We analyze linguistic metaphors in a corpus of news texts professionally simplified for different grade levels. While editors' guidelines instructed to avoid vivid metaphors, such as "paint into a corner", our goal was to find out whether, and if so, how, linguistic metaphors in general are simplified by professional editors. Since ultimately we want to build automated metaphor simplification models, the purpose of this study is to investigate whether metaphors in a corpus of professionally simplified text, that is, potential training data, are simplified in systematic ways. Specifically, we were interested in two questions: 1) What types of discourse modifications do editors perform when simplifying metaphorical language? (in other words, whether a well-defined set...

Metaphors in Text Simplification: To change or not to change, that is the question

“…Each Newsela article has five versions of different difficulty levels determined based on the Lexile 2 readability scores, which are used to measure the complexity of texts and assign them to appropriate grade levels. Using these parallel news texts allows for the quick identification of changed items to produce a dataset to which metaphor information is then added (Wolska and Clausen, 2017).…”

“…In the sampled documents, we annotated their occurrences in the original sentences as either metaphoric or not by following the guidelines of the metaphor identification procedure MIPVU (Steen et al, 2010). 4 The annotation in this study builds on Wolska and Clausen (2017), where it was carried out as follows: one author initially identified metaphoric items in a smaller subset of the data. All unclear cases were then discussed with the second author and either resolved or left unannotated.…”

“…SnapDragon is a cross of the tasty Honeycrisp apple and another kind that's easier Ø to grow. are six simplification options that were identified for metaphoric items in Wolska and Clausen (2017), which we now apply to non-metaphoric items as well. A word can be preserved (same metaphor/same non-metaphor) 9 , replaced by another word of the same metaphorical status (other metaphor for metaphoric items and other nonmetaphor for literal items), replaced by a word of opposite metaphorical status (changed to nonmetaphor for metaphors and changed to metaphor for literal items), rephrased with metaphorical language (phrase with metaphors) or without (phrase without metaphors), or removed (word removed).…”

Contextual Modulation for Relation-Level Metaphor Identification

“…Over the last couple of years, there has been an increasing interest towards metaphor processing and its applications, either as part of natural language processing (NLP) tasks such as machine translation (Koglin and Cunha, 2019), text simplification (Wolska and Clausen, 2017;Clausen and Nastase, 2019) and sentiment analysis (Rentoumi et al, 2012) or in more general discourse analysis use cases such as in analysing political discourse (Charteris-Black, 2011), financial reporting (Ho and Cheng, 2016) and health communication (Semino et al, 2018).…”

Proceedings of the Second Workshop on Figurative Language Processing

“…This intrigued many researchers to develop various automatic techniques to process metaphor in text. Metaphor processing has many potential applications, either as part of natural language processing (NLP) tasks such as machine translation (Koglin and Cunha, 2019), text simplification (Wolska and Clausen, 2017;Clausen and Nastase, 2019) and sentiment analysis or in more general discourse analysis use cases such as in analysing political discourse (Charteris-Black, 2011), financial reporting (Ho and Cheng, 2016) and health communication (Semino et al, 2018).…”