Abstract: Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language. Moreover, there is a dearth of annotated corpora for investigating the cross-linguistic variation of adposition semantics, or for building multilingual disambiguation systems. This paper presents a corpus in which all adpositions have been semantically annotated in Mandarin Chinese; to the best of our knowledge, this is the first Chinese corpus to be broadly annotated with adposition semantics. Our approach adapts a framework that defined a general set of supersenses according to ostensibly language-independent semantic criteria, though its development focused primarily on English prepositions (Schneider et al., 2018). We find that the supersense categories are well-suited to Chinese adpositions despite syntactic differences from English. On a Mandarin translation of The Little Prince, we achieve high inter-annotator agreement and analyze semantic correspondences of adposition tokens in bitext.

Introduction: Adpositions (i.e. prepositions and postpositions) include some of the most frequent words in languages like Chinese and English, and help convey a myriad of semantic relations of space, time, causality, possession, and other domains of meaning. They are also a persistent thorn in the side of second language learners owing to their extreme idiosyncrasy BIBREF1, BIBREF2. For instance, the English word in has no exact parallel in another language; rather, for purposes of translation, its many different usages cluster differently depending on the second language. Semantically annotated corpora of adpositions in multiple languages, including parallel data, would facilitate broader empirical study of adposition variation than is possible today, and could also contribute to NLP applications such as machine translation BIBREF3, BIBREF4, BIBREF5, BIBREF6, BIBREF7, BIBREF8, BIBREF9 and grammatical error correction BIBREF1, BIBREF10, BIBREF11, BIBREF12, BIBREF13, BIBREF14. This paper describes the first corpus with broad-coverage annotation of adpositions in Chinese. For this corpus we have adapted schneider-etal-2018-comprehensive Semantic Network of Adposition and Case Supersenses annotation scheme (SNACS; see sec:snacs) to Chinese. Though other languages were taken into consideration in designing SNACS, no serious annotation effort has been undertaken to confirm empirically that it generalizes to other languages. After developing new guidelines for syntactic phenomena in Chinese (subsec:adpositioncriteria), we apply the SNACS supersenses to a translation of The Little Prince (3 2 3), finding the supersenses to be robust and achieving high inter-annotator agreement (sec:corpus-annotation). We analyze the distribution of adpositions and supersenses in the corpus, and compare to adposition behavior in a separate English corpus (see sec:corpus-analysis). We also examine the predictions of a part-of-speech tagger in relation to our criteria for annotation targets (sec:adpositionidentification). The annotated corpus and the Chinese guidelines for SNACS will be made freely available online.

Question: What is the size of the corpus?
Answer: 20287