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of modality-dependent unanalyzed external surfaces works very well. When
the resulting proplets are stored in the Word Bank, any grammatically mean-
ingful order is lost proplet-externally. A time-linear order is (re-)introduced
by LA-think, which decodes the proplet-internal addresses to follow the gram-
matical relations between them. This order is also used by LA-speak.
3.5 Relating Kinds of Proplets to Traditional Parts of Speech
The data structure of proplets is completely general: they may be defined for
any set of attributes and any set of values, and still be processed by suitably
adapted LA-grammar rules based on pattern matching. However, the long-term
upscaling of a talking robot will only be successful if the basic functionality of
its artificial cognition is empirically correct - and one window for investigating
natural cognition is the analysis of natural language. Let us therefore examine
the empirical nature of proplets from a linguistic point of view.
The number and the properties of different kinds of proplets are closely re-
lated to the parts of speech (PoS) of traditional grammar. We are looking for
the minimal part of speech set required for a general computational model of
natural language communication.
Despite some considerable variation in the literature on grammar, the tradi-
tional parts of speech may be defined roughly as the following eight:
3.5.1 T RADITIONAL PARTS OF SPEECH
1. verb
Includes finite forms like sang and non-finite forms like singing or sung
of main verbs, as well as auxiliaries like was or had and modals like could
and should . Some traditional grammars treat non-finite verb forms as a
separate class called participle .
2. noun
Includes common nouns like table and proper names like Julia .Also,
count nouns like topic and mass nouns like wine are distinguished.
3. adjective
Includes determiners like a(n), the, some, all ,and my as well as ad-
nominals like little, black, and beautiful . Some traditional grammars treat
determiners as a separate class.
4. adverb
Includes adverbial modifiers like beautifully and intensifiers like very .
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