Constrained Natural Languages (CNLs) are becoming an increasingly popular way of writing technical documents such as requirements specifications. This is because CNLs aim to reduce the ambiguity inherent within natural languages, whilst maintaining their readability and expressiveness. The design of existing CNLs appears to be unfocused towards achieving specific quality outcomes, in that the m...

Much research has been devoted to the task of learning lexical classes from unannotated input text. Among the chief difficulties facing any approach to the unsupervised induction of lexical classes are that of token-level ambiguity and the classification of rare and unknown words. Following the work of previous authors, the initial stage of syntactic category induction is treated in the current...

1. Scope vs. Lexical Theory of Even The English focus particle even is known to introduce a scalar presupposition (ScalarP) given in (1); Alan even saw [Bill]F presupposes that ‘that Bill saw Alan’ is the least-likely proposition among alternatives (LeastP). In contexts where negative polarity items (NPIs) such as any can occur, we observe ambiguity; I doubt that Alan even saw [Bill]F is ambigu...

One important issue in neuroimaging research on language is how the brain processes and represents lexical semantics. Past studies with various paradigms reveal that the left inferior prefrontal and mid-superior temporal regions play a crucial role in semantic processing. Those studies, however, typically utilize words having a precise and dominant meaning as stimuli and have not manipulated le...

The posterior middle temporal gyrus (MTG) and inferior frontal gyrus (IFG) are two critical nodes of the brain's language network. Previous neuroimaging evidence has supported a dissociation in language comprehension in which parts of the MTG are involved in the retrieval of lexical syntactic information and the IFG in unification operations that maintain, select, and integrate multiple sources...

Current vector-space models of lexical semantics create a single “prototype” vector to represent the meaning of a word. However, due to lexical ambiguity, encoding word meaning with a single vector is problematic. This paper presents a method that uses clustering to produce multiple “sense-specific” vectors for each word. This approach provides a context-dependent vector representation of word ...

Recognizing idioms in a sentence is important to sentence understanding. This paper discusses the lexical knowledge of idioms for idiom recognition. The challenges are that idioms can be ambiguous between literal and idiomatic meanings, and that they can be “transformed” when expressed in a sentence. However, there has been little research on Japanese idiom recognition with its ambiguity and tr...