Prepositions are highly polysemous. Yet, little effort has been spent to develop languagespecific annotation schemata for preposition senses to systematically represent and analyze the polysemy of prepositions in large corpora. In this paper, we present an annotation schema for preposition senses in German. The annotation schema includes a hierarchical taxonomy and also allows multiple annotati...

In this paper, we show how a constraint-based approach influences the modelling of preposition lexicalization in natural language generation. We concentrate on the linguistic description, which is the most challenging. The CSP procedures themselves are then rather straightforward. Preposition choice depends on the verb and its requirements, on the one hand, and the characteristics of the NP the...

This paper introduces the problem of predicting semantic relations expressed by prepositions and develops statistical learning models for predicting the relations, their arguments and the semantic types of the arguments. We define an inventory of 32 relations, building on the word sense disambiguation task for prepositions and collapsing related senses across prepositions. Given a preposition i...

Prepositions are highly polysemous, and their variegated senses encode significant semantic information. In this paper we match each preposition’s complement and attachment and their interplay crucially to the geometry of the word vectors to the left and right of the preposition. Extracting such features from the vast number of instances of each preposition and clustering them makes for an effi...

This paper addresses an automatic classification of preposition types in German, comparing hard and soft clustering approaches and various windowand syntax-based co-occurrence features. We show that (i) the semantically most salient preposition features (i.e., subcategorised nouns) are the most successful, and that (ii) soft clustering approaches are required for the task but reveal quite diffe...

The paper describes an approach to automatically select from Indian Language the appropriate lexical correspondence of English simple preposition. The paper describes this task from a Machine Translation (MT) perspective. We use the properties of the head and complement of the preposition to select the appropriate sense in the target language. We later show that the results obtained from this a...

The phenomena of preposition stranding is very rare when examining various languages around the world. The most distinct class of languages that demonstrates this is that of the Germanic languages. Behavior within the Germanic languages varies from one language to the next. On the one end, Danish, as Herslund (1984:58) puts it, “...allows almost completely free stranding of prepositions.” Horns...

Prepositions are very common and very ambiguous, and understanding their sense is critical for understanding the meaning of the sentence. Supervised corpora for the preposition-sense disambiguation task are small, suggesting a semi-supervised approach to the task. We show that signals from unannotated multilingual data can be used to improve supervised prepositionsense disambiguation. Our appro...

In this paper, we present a supervised classification approach for disambiguation of preposition senses. We use the SemEval 2007 Preposition Sense Disambiguation datasets to evaluate our system and compare its results to those of the systems participating in the workshop. We derived linguistically motivated features from both sides of the preposition. Instead of restricting these to a fixed win...