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Deriving Semantic Meaning From Google Results
prostoalex writes "New Scientist talks about Paul Vitanyi and Rudi Cilibrasi of the National Institute for Mathematics and Computer Science in Amsterdam and their work to extract meaning of words from Google's index. The pair demonstrates an unsupervised clustering algorithm, which 'distinguish between colours, numbers, different religions and Dutch painters based on the number of hits they return', according to New Scientist."
Every language has "ambiguity", but ambiguity can come in different flavors (phonological, morphological, syntactic, semantic, pragmatic). Some of the chief instigators of language change can be thought of as ambiguity on these levels. So firstly, it's hard to imagine the existence of a function mapping languages to "ambiguity levels".
The motivation for your comment about English versus Spanish probably comes from the fact that you know of more English homophones than Spanish ones. Indeed, most literate people think of their language in terms of written words, so your take on the matter is common.
(As a slight digression, your example of right the direction versus right as in 'correct, just' is pretty interesting. We can understand the semantic similarity between the two when we notice that most humans are right-handed. Thus it is extraordinarily common, cross-linguistically and cross-culturally, for the word meaning the direction 'right' to have similar meanings as dextrous, just, well-guided and so on, whereas the word meaning the direction 'left' also has meanings such as worthless, stupid. (In fact, the word dextrous was borrowed through French from the Latin word dexter meaning 'right, dexterous' or dextra meaning 'right hand'.) So the given example is one where, historically, a word had no ambiguity, but gained ambiguity because speakers started using it differently.)
Getting back to the main topic, more problematic about Section 7 of TFA is the implicit assertion that, at some point in the future, their techniques can be applied to create a function mapping words in a particular language to words in another language. Anybody who has studied more than one language has seen cases where this is difficult to do on the word-level. For instance, the French equivalent of English river is often given as riviere or fleuve. But riviere is only used by French speakers to mean 'river or stream that runs into another river or stream' whereas fleuve means 'river or stream that runs into the sea'. English breaks up river-like things by size: rivers are bigger than streams. So, in the strictest sense, there is no English word for fleuve, just as there's no French word for stream (unless there has been a recent borrowing I don't know about). This certainly does not imply that French people can't tell the difference between big rivers and small rivers; their lexicon just breaks things up differently.
These little problems can be remedied lexically, as I've just done. So fleuve is denotationally equivalent to river or stream that runs into the sea, although the latter is obviously much bulkier than its French equivalent. The real problem is that there are words in some languages whose meanings are not encoded at all in other languages. English, for example, has a lexical past-progressive tense marker, was, used in the first person singular (e.g. I was running to the store). Some languages have no notion of tense. What, then, does was mean in the context of such a language?
It's pretty well-known that Slashdotters' general policy is to tear apart every article we read, and half of those we don't. This is certainly not my intent here. Languages are complicated beasties, and everyone seems to understand that, including the writers of the article. So, we should interpret their result in Section 7 as them saying, "Well, maybe this has gotten us a baby-step closer to creating the hypothetical Perfect Natural Language Translator, but someone's gonna have to do a lot more work to see where this thing goes".