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Between classical symbolic word sense disambiguation (wsd) using explicit deep semantic representations of sentences and texts and statistical wsd using word co-occurrence information, there is a recent tendency towards mediating methods. Similar to so-called lightweight semantics (Marek, 2009) we suggest to only make sparse use of semantic information. We describe an approximation model based upon flat underspecified discourse representation structures (FUDRSs, cf. Eberle, 2004) that weighs knowledge about context structure, lexical semantic restrictions and interpretation preferences. We give a catalogue of guidelines for human annotation of texts by corresponding indicators. Using this, the reliability of an analysis tool that implements the model can be tested with respect to annotation precision and disambiguation prediction and how both can be improved by bootstrapping the knowledge of the system using corpus information. For the balanced test corpus considered the recognition rate of the preferred reading is 80-90% (depending on the smoothing of parse errors).
This paper analyses reply relations in computer-mediated communication (CMC), which occur between post units in CMC interactions and which describe references between posts. We take a look at existing practices in the description and annotation of such relations in chat, wiki talk, and blog corpora. We distinguish technical reply structures, indentation structures, and interpretative reply relations, which include reply relations induced by linguistic markers. We sort out the different levels of description and annotation that are involved and propose a solution for their combined representation within the TEI annotation framework.
This paper analyses reply relations in computer-mediated communication (CMC), which occur between post units in CMC interactions and which describe references between posts. We take a look at existing practices in the description and annotation of such relations in chat, wiki talk, and blog corpora. We distinguish technical reply structures, indentation structures, and interpretative reply relations, which include reply relations induced by linguistic markers. We sort out the different levels of description and annotation that are involved and propose a solution for their combined representation within the TEI annotation framework.