By Manfred Stede
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To a large extent, this similarity is well-defined through a small set of lexical-semantic relations that dictionaries 11 By convention, we take as antecedent always the most recent coreferent expression. See Chapter 3 for a general introduction to coreference. 2. 3: Content words from second paragraph of suffering. N. employee report mission_chief country building code wipe_out neighborhood shoddy concrete structure hospital wreck port airport control_tower action damage key institution Presidential_Palace National_Cathedral kill archbishop senior politician cut_off power phone service block passage street heavy equipment capital use move debris trap survivor dig mass_grave go_wrong hospital_manager say (and semanticists) use to characterize the structure of our vocabulary, and which show up in many implemented thesauri and ontologies.
To illustrate this with just a few examples from research we have discussed above: Choi  points out that his clustering approach on his (synthetic) data performs better than Hearst’s text tiling. Dias et al.  show that on their data, text tiling is better than Choi’s clustering, and their own method is better still. Kauchak and Chen  point out that for narratives, text tiling yields almost random results, and other standard methods are hardly better. Etc. For authentic, non-synthetic text, ultimately we want to know more exactly how classes of text differ from each other and, accordingly, what means they employ to signal topic boundaries.
1 The example also illustrates the complication that referring expressions need not be disjoint in the text but can be embedded in one another, as with possessive noun phrases or with restrictive relative clauses when they are seen as part of the governing NP (in order to simplify, one could generally cut off the relative clauses, irrespective of their being restrictive or non-restrictive). As a shorthand, we occasionally call referring expressions pointing to a discourse referent mentions of that referent.