This paper presents a unification-based system for identifying words in Mandarin Chinese sentences. The information items in the knowledge base, including the lexicon, lexical rules, and execution results, are represented as feature structures, a set of fearnre-value pairs.
Unification is the primitive operation supported by the system.
Initially, information of the possible words in the input sentences is extracted by unifying the substrings in the input sentences with items of the lexicon. Words generated by morphological processes, such as reduplication and affixation, are identified by lexical rules. The ambiguous word strings are resolved by a number of ambiguity-resolution rules. Then, the survived segmentations are ranked by the Markov process. An HPSG-based chart parser is finally used to prune sentences with illegal syntactic and semantic constructions.