Prepositions and conjunctions are two of the largest remaining bottlenecks in parsing. Across various existing parsers, these two categories have the lowest accuracies, and mistakes made have consequences for downstream applications. Prepositions and conjunctions are often assumed to depend on lexical dependencies for correct resolution. As lexical statistics based on the training set only are ...

Can relations described by English nounnoun compounds be adequately captured by prepositions? We attempt to answer this question in a data-driven way, using gamification to annotate a set of about a thousand noun-noun compound examples. Annotators could make a choice out of five prepositions generated with the help of paraphrases found in the Google ngram corpus. We show that there is substanti...

Prepositions combine with nouns flexibly when describing concrete locative relations (e.g. at/on/in the school) but are rigidly prescribed when paired with abstract concepts (e.g. at risk; on Wednesday; in trouble). In the former case they do linguistic work based on their discrete semantic qualities, and in the latter they appear to serve a primarily grammatical function. We used the abstract ...

Many grammar checkers in rule-based approach do not handle errors that come from various usages, for example, the usages of prepositions. To study the behavior of prepositions, we introduce the language model into a grammarchecking task. A language model is trained from a large training corpus, which contains many short phrases. It can be used for detecting and correcting certain types of gramm...

This paper presents a corpus-based method for automatic evaluation of geometric constraints on projective prepositions. The method is used to find an appropriate model of geometric constraints for a twodimensional domain. Two simple models are evaluated against the uses of projective prepositions in a corpus of natural language dialogues to find the best parameters of these models. Both models ...

In this study, the use of most frequent spatial prepositions in English, Polish, Swedish, and Russian is analyzed. The prepositions and their contexts are extracted from corpora by means of concordance tools. The collostructional strength between the prepositions and the most frequent nouns in the PPs (Gries et al. 2005) is then computed in order to get a more detailed picture of the contexts i...

The need to communicate and reason about space is pervasive in human cognition. Consequently, most languages develop specialized terms for describing relationships between objects in space – spatial prepositions. However, the specific set of prepositions and the delineations between them vary widely. For example, in English containment relationships are categorized as in and support relationshi...

this study investigated the effect of applying the dynamic system theory (dst) and cognitive linguistics (cl) insights into grammar instruction on efl learners’ learning of english prepositions and learner autonomy. sixty iranian efl learners at the lower-intermediate level of language proficiency were randomly assigned to 1 experimental and 1 control group. the 2 groups filled out an autonomy ...

This paper addresses vector space models of prepositions, a notoriously ambiguous word class. We propose a rank-based distance measure to explore the vector-spatial properties of the ambiguous objects, focusing on two research tasks: (i) to distinguish polysemous from monosemous prepositions in vector space; and (ii) to determine salient vector-space features for a classification of preposition...