There remain some constructions that just require an understanding of the document or the way the world is for them to be correctly translated. For many purposes it doesn't matter, but if the system were analysing witness statements to initiate a search, it could be crucial. The other damning factor was the over-selling of systems. Research projects have to secure long-term funding in order to keep research teams together. In a situation where there are many teams working on the same basic area, it is crucial to be seen to be making good progress.
Sponsors like to see clear practical demonstrations of the results of their funding.
Machine Translation suffered from over selling itself up until the mid-1960s. For Machine Translation, the demonstration of the Georgetown system on 7th January 1955 was just such an occasion. Looking back on this system with the hindsight of forty years, it seems an incredibly crude system that never had a hope of translating any by the most carefully chosen texts. At the time, it was greeted as the advent of practical Machine Translation. This had the knock-on effect of halting funding in other countries and NLP entered something of a dormant phase.