Abstract: A method comprising reacting an alkane gas with a halogen gas in a halogenations reactor to form a halogenation reaction product mixture comprising alkane halide and hydrogen halide mixture; mixing the halogenations reaction product mixture with a countercurrent flow of a metal organic salt thereby forming an extractor product mixture of a metal halide, organic salt, and organic acid separating the organic ester and organic acid mixture from the metal halide; oxygenating the metal halide to form a metal oxide and halide containing gasses; separating the metal oxide from the halide containing gasses; mixing the metal oxide with water to form a metal oxide slurry; mixing the metal oxide slurry with a countercurrent flow of the organic ester and organic acid mixture to form a raw product comprising alkanol, a metal organic salt is provided.

Abstract: Described is method, the Latent Words Language Model (LWLM), that automatically determines context-dependent word distributions (called hidden or latent words) for each word of a text. The probabilistic word distributions reflect the probability that another word of the vocabulary of a language would occur at that position in the text. Furthermore, a method is described to use these word distributions in statistical language processing applications, such as information extraction applications (for example, semantic role labeling, named entity recognition), automatic machine translation, textual entailment, paraphrasing, information retrieval, and speech recognition.