We present a computer-assisted language learning (CALL) system that generates fill-in-the-blank items for preposition usage. The system takes a set of carrier sentences as input, chooses a preposition in each sentence as the key, and then automatically generates distractors. It personalizes item selection for the user in two ways. First, it logs items to which the user previously gave incorrect...

We present a preliminary study on unsupervised preposition sense disambiguation (PSD), comparing different models and training techniques (EM, MAP-EM with L0 norm, Bayesian inference using Gibbs sampling). To our knowledge, this is the first attempt at unsupervised preposition sense disambiguation. Our best accuracy reaches 56%, a significant improvement (at p <.001) of 16% over the most-freque...

What these examples illustrate is that a particular Trajector (TR) can, in conjunction with a particular Landmark (LM), affect the interpretation of a preposition. On one hand, the interpretation ascribed to the sentence in (1) is that the LM, the bowl, contains or surrounds the TR, the fruit. On the other hand, in (2) the conventional interpretation is that the TR, the crack, constitutes a fla...

We present the first corpus annotated with preposition supersenses, unlexicalized categories for semantic functions that can be marked by English prepositions (Schneider et al., 2015). That scheme improves upon its predecessors to better facilitate comprehensive manual annotation. Moreover, unlike the previous schemes, the preposition supersenses are organized hierarchically. Our data will be p...

this paper is an attempt to explore the prepositions used to encode the agent in persian passive constructions. according to givón (1983) the main function of the passive constructions is to defocus the agent. as the general trend in persian is to omit this defocused agent, we will stylistically divide the passive constructions into two main sub branches, namely unmarked and marked passives acc...

We evaluate the effect of adding parse features to a leading model of preposition usage. Results show a significant improvement in the preposition selection task on native speaker text and a modest increment in precision and recall in an ESL error detection task. Analysis of the parser output indicates that it is robust enough in the face of noisy non-native writing to extract useful information.

This paper presents a lexical account of the syntax of Sorani Kurdish prepositions within the framework of Head-Driven Phrase Structure Grammar (HPSG). Kurdish dialects have a rich class of prepositions and prepositional collocations with a complex syntactic behavior (Edmonds 1955, Mackenzie 1961). This situation results from severla factors. The first one involves the constitution of this clas...