Katja Markert

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We investigate the task of learning models for visual object recognition from natural language descriptions alone. The approach contributes to the recognition of fine-grain object categories, such as animal and plant species, where it may be difficult to collect many images for training, but where textual descriptions of visual attributes are readily(More)
We present the first effort towards producing an Arabic Discourse Treebank, a news corpus where all discourse connectives are identified and annotated with the discourse relations they convey as well as with the two arguments they relate. We discuss our collection of Arabic discourse connectives as well as principles for identifying and annotating them in(More)
We reformulate metonymy resolution as a classification task. This is motivated by the regularity of metonymic readings and makes general classification and word sense disambiguation methods available for metonymy resolution. We then present a case study for location names, presenting both a corpus of location names annotated for metonymy as well as(More)
We compare two ways of obtaining lexical knowledge for antecedent selection in other-anaphora and definite noun phrase coreference. Specifically, we compare an algorithm that relies on links encoded in the manually created lexical hierarchy WordNet and an algorithm that mines corpora by means of shallow lexico-semantic patterns. As corpora we use the(More)