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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 presents types and annotation layers of reply relations in computer- mediated communication (CMC). Reply relations hold between post units in CMC interactions and describe references from one given post to a previous post. We classify three types of reply relations in CMC interactions: first, technical replies, i. e. the possibility to reply directly to a previous post by clicking a ‘reply’ button; second, indentations, e. g. in wiki talk pages in which users insert their contributions in the existing talk page by indenting them and third, interpretative reply relations, i. e. the reply action is not realised formally but signalled by other structural or linguistics means such as address markers ‘@’, greetings, citations and/or Q-A structures. We take a look at existing practices in the description and representation of such relations in corpora and examples of chat, Wikipedia talk pages, Twitter and blogs. We then provide an annotation proposal that combines the different levels of description and representation of reply relations and which adheres to the schemas and practices for encoding CMC corpus documents within the TEI framework as defined by the TEI CMC SIG. It constitutes a prerequisite for correctly identifying higher levels of interactional relations such as dialogue acts or discussion trees.