moses

It's a simple one-off experiment, and compared to real statistical machine translation with Moses on the same data the translation is pretty much instant.

The phrase table was built with Moses from the Europarl parallel corpus [0] minus the texts.

Maybe you want to read a little about Robert Moses and then come back here.

I think it was Robert Moses who decided to raze Radio Row to build WTC.

I get trying to humanize stories, but Moses Weisberg does nothing for this story.

I would love to see an OCaml alternative to Prophet/MoSes using stuff like this...

Straight from Wikipedia: > Close associates of Moses claimed that they could keep African Americans from using pools in white neighborhoods by making the water too cold.

Was Moses a political or religious leader?

Here's an example I tried with CPython2, 3 and PyPy yesterday: It loads the most probable translations for all unigrams from a Moses phrase translation table (11GB) into a dict, and using that dict translates 73 MB of text word by word.

Even a few scribbled pages of notes about common moral questions ("is killing in self-defence murder?", "do Moses's instructions to commit genocide override the commandments?") would have been helpful.

I can demonstrate that it's used by people west of the Mississippi, such as: > "Two nationally recognized cattle handling experts, Tom Noffsinger and Curt Pate, will be in Moses Lake[, Washington]...

We studied Moses and we ran through the "man laying down with another man being detestable to God" passage and the study notes didn't really address it directly other than to say God gave the people sexual purity laws and you gotta pray about it and decide for yourself.

Moses' involvement in road planning around New York hardly makes him the architect of the interstate system.

Moses needs something on the order of 1600 CPU-hours (50 nodes * 8 threads * 4 hours).

Also there is a program called After Egypt which is a game he made based on the story of Moses.