VOLIMET : A Parallel Corpus of Literal and Metaphorical Verb-Object Pairs for E nglish– G erman and E nglish– F rench (2024)

Abstract: The interplay of cultural and linguistic elements that characterizes metaphorical language poses a substantial challenge for both human comprehension and machine processing. This challenge goes beyond monolingual settings and becomes particularly complex in translation, even more so in automatic translation. We present VOLIMET, a corpus of 2,916 parallel sentences containing gold standard alignments of metaphorical verb-object pairs and their literal paraphrases, e.g., tackle/address question, from English to German and French. On the one hand, the parallel nature of our corpus enables us to explore monolingual patterns for metaphorical vs. literal uses in English. On the other hand, we investigate different aspects of cross-lingual translations into German and French and the extent to which metaphoricity and literalness in the source language are transferred to the target languages. Monolingually, our findings reveal clear preferences in using metaphorical or literal uses of verb-object pairs. Cross-lingually, we observe a rich variability in translations as well as different behaviors for our two target languages.

## introduction metaphor is a figurative device which allows us to understand and experience one (typically abstract) domain in terms of another (typically more concrete) domain @xcite . for example, in the sentence i'll tackle the challenging problem of metaphors in translation, the abstract domain of dealing with a problem is expressed in terms of the more concrete domain of physically seizing and throwing down something/someone. metaphorical language has long been recognized as a challenge for both human understanding and machine processing @xcite and is not confined to monolingual settings. it extends into cross-lingual territory, particularly in the realm of translation, where metaphors represent a hard nut to crack: they are not only very flexible in their structures and meanings, but also strongly depend on the involved languages and cultures @xcite . while the effort to automate the translation of figurative language using machine translation (mt) systems is underway, limited mt research explores the contrast between metaphorical and literal language in translation and its potential effect on translatability (van den @xcite and variability @xcite in language production and generation. to bridge this gap, we create volimet, a parallel corpus of english-german and english-french sentences containing gold standard alignments of paraphrased metaphorical and literal uses of verb-object (vo) pairs (see example in fig. 1 ). the corpus provides insights on the translation of metaphorical vo pairs and their corresponding literal paraphrases from the source language (sl) english, to the target languages (tl) french and german. for instance, given the metaphorical vo tackle question, is its literal vo counterpart address question equally frequent in natural language? how is it translated into other languages and to which extent is the metaphoricity transferred or preserved in the translation from sl to tl? how many different translations of this vo do humans produce, i.e., do we find one-to-one or one-to-many mappings between source and target languages? in this paper, we present a comprehensive account of the corpus construction process and perform extensive monolingual and cross-lingual analyses. monolingually, we seek to uncover patterns in the use of metaphorical vs. literal vos. we find that considering the verb and its object as a unit provides a more nuanced representation than considering the verb on its own, crucial for accurate automatic processing. cross-lingually, we observe a rich tapestry of translation variability, indicating one-to-many mappings between the source vos and their target translations, where both metaphorical and literal uses are prevalent in the tls. we further uncover differences in translations between the tls, highlighting the need for flexible mt systems capable of reproducing this diversity. overall, our parallel corpus is meticulously crafted to encapsulate all these intricacies and represents a key resource in the endeavor to tackle the challenges posed by metaphorical language. in the future, it will also be of great use for machine translation research on metaphors. ## related work translation studies metaphorical language represents an extremely common phenomenon @xcite and has been of interest in translation studies when prescribing conditions for translating metaphors @xcite . as of today, the three translation modes from @xcite remain the core choices in tl translations of sl metaphors: (1) a translation "sensu stricto" as in le jour tombe-der tag fällt (lit. the day falls), which might lead to a semantic anomaly or innovation if the metaphor vehicles in sl and tl differ, (2) an onomasiological translation referred to as "substitution" where the sl and tl vehicles are translation equivalents sharing the same tenor, as in le jour tombe-die nacht bricht (her)ein (lit. the night falls in); and (3) a discursive, non-metaphorical translation "paraphrase" as in le jour tombe-es wird abend (lit. it is becoming night). machine translation mt research incorporating figurative language has mainly been restricted to studies on the translation of structurally or seman-tically less flexible expressions, such as idioms @xcite and multi-word-expressions (e.g., noun compounds such as flea market; particle verbs such as give up; support verb constructions such as play a role) @xcite . cognitive linguistics @xcite and @xcite provide evidence for the cognitive function of metaphors in contrast to their literal counterparts, by demonstrating that people tend to use metaphors to explicate things. metaphorical language tends to also be more emotionally-loaded than literal language (citron and goldberg, 2014; @xcite and may influence the way people conceptualize the world @xcite . overall, there is empirical evidence for differences in using metaphorical in contrast to literal language, which we explore from a crosslingual perspective in this work. nlp research has mainly focused on metaphor detection @xcite and interpretation @xcite , with the predominant idea to generate literal paraphrases for metaphorical expressions. more recently and more closely related to the current interest of this present work, we built a dataset of verb-object and subject-verb metaphorical vs. literal expressions used in large context and collected via crowd-sourcing annotations @xcite . in further work, we compared adapted computational models for discourse metaphor/literal interactions; the results from the human judgements showed the equal importance of metaphorical and literal usages, a behavior that computational models fail at mimicking @xcite . this reinforces the necessity for a more nuanced approach and attests limitations of word representations for metaphorically-used language. overall, rich interdisciplinary research offers insights on metaphors in monolingual settings, but less so in cross-lingual settings. our work contributes to filling this gap by looking at the contrast of metaphorical and literal language, both from a monolingual and cross-lingual perspective. ## creating volimet we create volimet, a comprehensive linguistic resource comprising various components that are necessary to enhance not only our understanding of metaphorical language use but also its effect on translated text. volimet encompasses an extensive collection of english metaphorical and literal vo pairs, as in tackle vs. address question, thoughtfully curated to provide paraphrases of one another ( §3.1). volimet also significantly enhances its contribution by offering english sentences featuring these vo pairs, meticulously extracted from parallel data ( §3.2). the parallel nature of volimet allows on the one hand monolingual analyses of metaphorical and literal vo pairs in context. on the other hand, it also enables a cross-lingual exploration of how these vos are translated into german and french, making volimet the first resource of metaphorical and literal vos and their respective translations. ## quantitative analyses volimet encompasses close to 3,000 en2fr and en2de parallel sentences containing a total of 114 metaphorical and literal vo pairs. we first perform in-depth monolingual ( § 4.1) and cross-lingual ( § 4.2) quantitative analyses. monolingually, we shed light on the frequency of our vos, their syntactic (non-)fixedness and the contrast in their metaphorical vs. literal usages. cross-lingually, we look at the variability across translations. then we explore whether metaphoricity vs. literalness in english is transferred to french and german during the translation process, and how the findings differ between the two tls. ## discussion vos frequency from our original 297 metaphorical vs. literal vo pairs, there were more literal vos which were extracted from the source part of our parallel corpus (75 vs. 58). for some vo pairs we find clear preferences for one option over the other, i.e., either the metaphorical or the literal vo of a pair is clearly more frequent. for instance, the metaphorical vos tackle crisis/challenge are nine times more frequent than their literal paraphrases address crisis/challenge. one might think that this phenomenon has to do with the verb only, e.g., tackle is always favored over address. this is however not the case as address is favored over tackle when combined with other objects (e.g., problem, concern). for computational tasks such as text generation or machine translation, this finding gives support to the necessity to consider a verb along with its object: when considering paraphrases, one cannot rely on the frequency of the verb only, as more nuance might be brought by whichever argument is used along with that verb. this finding should be taken with a grain of salt because we are lacking data points to gener-alize across vo pairs. for instance, the verb pair grasp/understand only occurs with the object point in our data, and while the metaphorical usage grasp is favored over its literal counterpart, we do not know whether we would observe similar behaviors with other objects (e.g., meaning, concern, etc.) of that verb pair. vos syntactic variation looking at syntactic variations can shed light on (i) whether there are some clearly lexicalized vos, but also (ii) whether there exist discrepancies between the paraphrase vo pairs, where one variant is more lexicalized than its paraphrase. unlike idioms, metaphors are considered (syntactically) more flexible expressions that retain their metaphorical meaning if they undergo syntactic variations @xcite . for example, it's raining cats and dogs cannot be replaced by it's raining a cat and a dog without losing its idiomatic interpretation. we however expect to observe a metaphorical vo such as tackle question in different morphosyntactic forms, as in tackling the questions or the question was tackled, where the (metaphorical) meaning remains intact. we have observed that both metaphorical and literal vos that appear more than once in the data present up to eight different syntactic variations (three on average). none of the vos therefore presents clear signs of syntactic fixedness, but there also exists no clear discrepancy in syntactic flexibility between metaphorical and literal vos. in other words, this finding suggests that amongst our paraphrased pairs, there is complete consistency in terms of (non-)lexicalization. variability in translation as we discussed in the two previous paragraphs, we observe quite some diversity in the use of metaphorical vs. literal vo pairs in the source language, both in terms of frequency and syntactic variations. indeed, we saw that some vos present a preference for either the metaphorical or literal variant (see figure 2 ), and that vos display many inflections. is this diversity encountered in the sl also observed in the french and german translations, respectively? we observe many syntactic variations in translation for both en2fr and en2de, indicating that the syntactic structure of the source vo is therefore not necessarily respected in the translation process. for example, the verb-object construction break agreement is translated as a noun-preposition-noun construction into french (rupture de accord, lit. breaking of agreement). regarding variability, we have seen that each source vo, regardless of its metaphoricity, is on average aligned to four translations, in both language pairs. only very few vos occurring more than once in the parallel corpus correspond to a one-to-one translation. not only does this confirm that there are many ways to transfer one concept from one language to another, but also that humans tend to be very creative in the way they produce language. in other words, we generally find (large) variability in translation per sl concept (see section 4.2). we also notice slightly less variability in translation per literal vo than per metaphorical vo, i.e., one-to-many translations are more frequent for metaphorical vos than for literal vos. for example, the metaphorical concept of boost in boost economy does not have a sensu stricto metaphorical translation in french; we observed seven different translations for the 15 instances of the source metaphorical vo. however, we found only one (sensu stricto) french translation of the literal paraphrase improve economy. it therefore seems that if a metaphor in the sl does not have an equivalent in the tl, translators seem to show more creativity in their translation process. this perspective is especially interesting to keep in mind for natural language processing downstream tasks such as mt. unlike the translation of idioms, which is either right or wrong @xcite @xcite , efforts should be focused on building mt systems which are able to be more nuanced with respect to the use of metaphors. ## conclusion we presented volimet, the first parallel corpus of english-german and english-french paraphrased metaphorical and literal verb-object pairs. besides offering a novel lexicon of 297 metaphorical vs. literal vo paraphrase pairs, volimet also provides their cross-lingual contexts at the sentence level. we conducted substantial human work to provide gold standard alignments of source vos to all their corresponding translations. we performed quantitative and qualitative analyses from both a monolingual and cross-lingual perspective. monolingually, we showed that for some vo pairs, there exists a clear preference for either the metaphorical or the literal variant. it is however crucial to consider the verb and its object as a unit, as we observed apparent differences in behaviors when the verb is considered with or without its object. cross-lingually, our findings revealed substantial variability in translations, i.e., one-to-many mappings between source vos and their target translations. finally, we investigated the extent to which metaphoricity/literalness gets preserved in the translation process. we found different behaviors between our two target languages, where french translations show equal use of metaphorical and literal language, while german tends to favor literal translations by a large margin.