If we want the computer to really understand text, a new way of processing language is needed
-Stephen Clark
The verb run has 606 different meanings. It’s the largest single entry in the Oxford English Dictionary, placing it ahead of set, at 546 meanings.
Although words with multiple meanings give English a linguistic richness, they can also create ambiguity: putting money in the bank could mean depositing it in a financial institution or burying it by the riverside; drawing a gun could mean pulling out a firearm or illustrating a weapon.
We can navigate through this potential confusion because our brain takes into account the context surrounding words and sentences. So, if putting money in the bank occurs in a context that includes words like savings and investment, we can guess the meaning of the phrase. But, for computers, so-called lexical ambiguity poses a major challenge.
“Ambiguity is the greatest bottleneck to computational knowledge acquisition, the killer problem of all natural language processing,” explained Dr Stephen Clark. “Computers are hopeless at disambiguation – at understanding which of multiple meanings is correct – because they don’t have our world knowledge.”
Clark leads two large-scale research projects – recently funded by the Engineering and Physical Sciences Research Council and the European Research Council – that hope to overcome this bottleneck. Applications of the research include improved internet searching, machine translation, and automated essay marking and summarisation.
Read the full story
Image: Words Credit: jah on flickr
Reproduced courtesy of the University of Cambridge
______________________________________________________