Grammatical Features Inventory: Aspect

In attempting to understand language, many researchers use features, the elements
into which linguistic units, such as words, can be broken down. Examples of features
are NUMBER (singular, plural, dual, ...), PERSON (1st, 2nd, 3rd), and TENSE (present,
past, ...). Features have proved invaluable for analysis and description, and have a
major role in contemporary linguistics, from the most abstract theorising to the most
applied computational applications. Yet little is firmly established about features:
we have no inventory of which features are found in the world's languages, no agreed
account of how they operate across different components of language, no certainty on
how they interact, and thus no general theory of features. They are used, but are
little discussed and poorly understood. This is a central gap in the conceptual
underpinning of much linguistic investigation.

The Grammatical Features Inventory is an attempt to put the notion of linguistic
'feature' on a sounder empirical and conceptual base. It aims to provide evidence for
the diverse content of features in the world's languages, as well as discuss some of
their formal properties, particularly in morphology (word structure) and syntax
(sentence structure).

The term 'aspect' designates the perspective taken on the internal temporal organisation of the situation, and so 'aspects' distinguish different ways of viewing the internal temporal constituency of the same situation (Comrie 1976:3ff, after Holt 1943:6; Bybee 2003:157). The 'situation' is meant here as general term covering events, processes, states, etc., as expressed by the verb phrase or the construction. Unlike tense, which is situation-external time, aspect is situation-internal and non-deictic, as it is not concerned with relating the time of the situation to any other time point.

This resource was created for the project 'Grammatical features: A key to
understanding language', funded by the Economic and Social Research Council under
grant number RES-051-27-0122. This support is gratefully acknowledged.