 Other landmarks include research on default feature specification in syntactic theory and default lexical inheritance (e.g., Gazdar et al. 1985; Boguraev &amp; Pustejovsky 1990; Lascarides et al. 1996), where default inheritance comes from a simple idea pertaining to all taxonomies: regular features belonging to an entity of a certain type are inherited from the categories higher up in the taxonomic hierarchy, that is simply by virtue of the membership of a certain ontological type. As a result, only the non-default features have to be attended to (on various semantic networks in computational linguistics see also Stone 2016). To generalize, this line of research can lead to incorporation of information into logical forms, including, as can be seen in the example of SDRT, dynamic logical forms of discourses. In a different camp there are statistical, distributional approaches to meaning where meaning is derived from information about co-occurrence of items gleaned from corpora and then quantitatively analysed. This orientation gave rise to current vector-based approaches (see, e.g., Jurafsky &amp; Martin 2017 [Other Internet Resources]; Coecke et al. 2010 and for discussion Liang &amp; Potts 2015). Vector semantics exploits the finding that dates back at least to Harris (1954) and Firth (1957) that the meaning of a word can be computed from the distribution of the words in its immediate context. The term ‘vector semantics’ derives from the representation of the quantitative values in this distribution called a ‘vector’, where the latter is defined as a distributional model that presents information in the form of a co-occurrence matrix. Vectors have been around since the 1950s but it is only recently that such distributional methods have been combined with logic-based approaches to meaning (see Liang &amp; Potts 2015). Vectors can measure the similarity of texts with respect to a lexical item, the similarity of lexical items with respect to sources, or, what interests us most, the co-occurrence of selected words in a selection of contexts (using additional methods to rule out co-occurrence by chance). In distributional semantics therefore the salient or default meaning is the meaning given by the observed high co-occurrence or, in other words, delimited by the high conditional probability of its occurrence in the context of other words.