The output of my word alignment file looks as such:
I wish to say with regard to the initiative of the Portuguese Presidency that we support the spirit and the political intention behind it . In bezug auf die Initiative der portugiesischen Präsidentschaft möchte ich zum Ausdruck bringen , daß wir den Geist und die politische Absicht , die dahinter stehen , unterstützen . 0-0 5-1 5-2 2-3 8-4 7-5 11-6 12-7 1-8 0-9 9-10 3-11 10-12 13-13 13-14 14-15 16-16 17-17 18-18 16-19 20-20 21-21 19-22 19-23 22-24 22-25 23-26 15-27 24-28
It may not be an ideal initiative in terms of its structure but we accept Mr President-in-Office , that it is rooted in idealism and for that reason we are inclined to support it . Von der Struktur her ist es vielleicht keine ideale Initiative , aber , Herr amtierender Ratspräsident , wir akzeptieren , daß sie auf Idealismus fußt , und sind deshalb geneigt , sie mitzutragen . 0-0 11-2 8-3 0-4 3-5 1-6 2-7 5-8 6-9 12-11 17-12 15-13 16-14 16-15 17-16 13-17 14-18 17-19 18-20 19-21 21-22 23-23 21-24 26-25 24-26 29-27 27-28 30-29 31-30 33-31 32-32 34-33
How can I produce the phrase tables that are used by MOSES from this output?
In this pdf, it explains the consistent phrase
extraction: http://www.inf.ed.ac.uk/teaching/courses/mt/lectures/phrase-model.pdf but what is the algorithm to achieve the phrases? (slide 16-21)
n! * m! * n * m
cells to check through for every sentence, where n and m are length of the source and target sentence. – Sarinasarine