We present a cost-based (or energy-based) model of disambiguation. When a sentence is ambiguous, a parse with the least cost is chosen from among multiple hypotheses. Each hypothesis is assigned a cost which is added when: (1) a new instance is created to satisfy reference success, (2) links between instances are created or removed to satisfy constraints on concept sequences, and (3) a concept node with insufficient priming is used for further processing. This method of ambiguity resolution is implemented in DMT~NS PLUS, which is a second generation bi-direetional English/Japanese machine translation system based on a massively parallel spreading.
