Hi Lakysha There has been very little change in the moses server.
Try running the following before you launch moses server export XMLRPC_TRACE_XML=1 and you should get a dump of the xmlrpc messages. This may help you debug the problem, cheers - Barry On 09/04/14 20:47, Lakshya wrote: > Hi Everybody, > > I am also facing problem with Mosesdecoder.v211 moseserver. I have > compiled the moseserver with out any error and the moseserver is > listenening to the port also. But when a translation request is going > from the interface, there is no responds from the mosesserver. > > I am getting the folowing exception.. > org.apache.xmlrpc.XmlRpcException: Failed to read server's response: > Connection refused > > Is there any difference in the moseswerver connection of Mosesdecoder > Release 1.0 and Mosesdecoder.V211. ? > > > > could anybody please clarify these doubts and how can I establish the > moseserver connection.. > > > Regards > Lakshya > > Message: 1 > Date: Mon, 7 Apr 2014 18:25:35 +0100 > From: kamel nebhi <[email protected] > <mailto:[email protected]>> > Subject: [Moses-support] moses server segmentation fault (core dumped) > To: moses-support <[email protected] <mailto:[email protected]>> > Message-ID: > <CAG66Y3c2UFq5+ > [email protected] > <mailto:jgxfwng%[email protected]>> > Content-Type: text/plain; charset="utf-8" > > Hi, > > I try to install mosesserver on localhost. I have installed xml-rpc and > rebuild moses with no problem. > > Next i use this command to run the server : > *~/mosesdecoder/bin/mosesserver > -f working/model/moses.ini --server-port 8999* > > But it failed with this message : > > Defined parameters (per moses.ini or switch): > config: /home/kamelnebhi/recaser/training/moses.ini > distortion-limit: 6 > feature: UnknownWordPenalty WordPenalty PhrasePenalty > PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 > path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0 > output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > input-factors: 0 > mapping: 0 T 0 > weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2 > TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5 > /home/kamelnebhi/mosesdecoder/bin > line=UnknownWordPenalty > FeatureFunction: UnknownWordPenalty0 start: 0 end: 0 > line=WordPenalty > FeatureFunction: WordPenalty0 start: 1 end: 1 > line=PhrasePenalty > FeatureFunction: PhrasePenalty0 start: 2 end: 2 > line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz > input-factor=0 output-factor=0 > FeatureFunction: TranslationModel0 start: 3 end: 6 > line=Distortion > FeatureFunction: Distortion0 start: 7 end: 7 > line=KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > FeatureFunction: LM0 start: 8 end: 8 > Loading the LM will be faster if you build a binary file. > Reading /home/kamelnebhi/recaser/training//cased.srilm.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > *The ARPA file is missing <unk>. Substituting log10 probability -100. > *************************************************************************************************** > Loading UnknownWordPenalty0 > Loading WordPenalty0 > Loading PhrasePenalty0 > Loading Distortion0 > Loading LM0 > Loading TranslationModel0 > Start loading text SCFG phrase table. Moses format : [3.69361] seconds > Reading /home/kamelnebhi/recaser/training/phrase-table.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > **************************************************************************************************** > Erreur de segmentation (core dumped) > root@kamelnebhi-MacBookPro:/home/kamelnebhi# > /home/kamelnebhi/mosesdecoder/bin/mosesserver -f > /home/kamelnebhi/recaser/training/moses.ini --server-port 80 > Defined parameters (per moses.ini or switch): > config: /home/kamelnebhi/recaser/training/moses.ini > distortion-limit: 6 > feature: UnknownWordPenalty WordPenalty PhrasePenalty > PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 > path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0 > output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > input-factors: 0 > mapping: 0 T 0 > weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2 > TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5 > /home/kamelnebhi/mosesdecoder/bin > line=UnknownWordPenalty > FeatureFunction: UnknownWordPenalty0 start: 0 end: 0 > line=WordPenalty > FeatureFunction: WordPenalty0 start: 1 end: 1 > line=PhrasePenalty > FeatureFunction: PhrasePenalty0 start: 2 end: 2 > line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz > input-factor=0 output-factor=0 > FeatureFunction: TranslationModel0 start: 3 end: 6 > line=Distortion > FeatureFunction: Distortion0 start: 7 end: 7 > line=KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > FeatureFunction: LM0 start: 8 end: 8 > Loading the LM will be faster if you build a binary file. > Reading /home/kamelnebhi/recaser/training//cased.srilm.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > *The ARPA file is missing <unk>. Substituting log10 probability -100. > *************************************************************************************************** > Loading UnknownWordPenalty0 > Loading WordPenalty0 > Loading PhrasePenalty0 > Loading Distortion0 > Loading LM0 > Loading TranslationModel0 > Start loading text SCFG phrase table. Moses format : [3.69152] seconds > Reading /home/kamelnebhi/recaser/training/phrase-table.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > **************************************************************************************************** > Segmentation fault (core dumped) > > *Thanks for your help* > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > http://mailman.mit.edu/mailman/private/moses-support/attachments/20140407/82302fab/attachment-0001.htm > > ------------------------------ > > ---------- Forwarded message ---------- > From: <[email protected] > <mailto:[email protected]>> > Date: Tue, Apr 8, 2014 at 3:57 AM > Subject: Moses-support Digest, Vol 90, Issue 19 > To: [email protected] <mailto:[email protected]> > > > Send Moses-support mailing list submissions to > [email protected] <mailto:[email protected]> > > To subscribe or unsubscribe via the World Wide Web, visit > http://mailman.mit.edu/mailman/listinfo/moses-support > or, via email, send a message with subject or body 'help' to > [email protected] <mailto:[email protected]> > > You can reach the person managing the list at > [email protected] <mailto:[email protected]> > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Moses-support digest..." > > > Today's Topics: > > 1. moses server segmentation fault (core dumped) (kamel nebhi) > 2. Re: Monolingual Word alignment (Philipp Koehn) > 3. Call for Participation: Automatic and Manual Metrics for > Operational Translation Evaluation (Lucia Specia) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 7 Apr 2014 18:25:35 +0100 > From: kamel nebhi <[email protected] > <mailto:[email protected]>> > Subject: [Moses-support] moses server segmentation fault (core dumped) > To: moses-support <[email protected] <mailto:[email protected]>> > Message-ID: > > <CAG66Y3c2UFq5+2w4eV00RrwVrMWTtVxpQ7=jgxfwng+afnr...@mail.gmail.com > <mailto:jgxfwng%[email protected]>> > Content-Type: text/plain; charset="utf-8" > > Hi, > > I try to install mosesserver on localhost. I have installed xml-rpc and > rebuild moses with no problem. > > Next i use this command to run the server : > *~/mosesdecoder/bin/mosesserver > -f working/model/moses.ini --server-port 8999* > > But it failed with this message : > > Defined parameters (per moses.ini or switch): > config: /home/kamelnebhi/recaser/training/moses.ini > distortion-limit: 6 > feature: UnknownWordPenalty WordPenalty PhrasePenalty > PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 > path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0 > output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > input-factors: 0 > mapping: 0 T 0 > weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2 > TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5 > /home/kamelnebhi/mosesdecoder/bin > line=UnknownWordPenalty > FeatureFunction: UnknownWordPenalty0 start: 0 end: 0 > line=WordPenalty > FeatureFunction: WordPenalty0 start: 1 end: 1 > line=PhrasePenalty > FeatureFunction: PhrasePenalty0 start: 2 end: 2 > line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz > input-factor=0 output-factor=0 > FeatureFunction: TranslationModel0 start: 3 end: 6 > line=Distortion > FeatureFunction: Distortion0 start: 7 end: 7 > line=KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > FeatureFunction: LM0 start: 8 end: 8 > Loading the LM will be faster if you build a binary file. > Reading /home/kamelnebhi/recaser/training//cased.srilm.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > *The ARPA file is missing <unk>. Substituting log10 probability -100. > *************************************************************************************************** > Loading UnknownWordPenalty0 > Loading WordPenalty0 > Loading PhrasePenalty0 > Loading Distortion0 > Loading LM0 > Loading TranslationModel0 > Start loading text SCFG phrase table. Moses format : [3.69361] seconds > Reading /home/kamelnebhi/recaser/training/phrase-table.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > **************************************************************************************************** > Erreur de segmentation (core dumped) > root@kamelnebhi-MacBookPro:/home/kamelnebhi# > /home/kamelnebhi/mosesdecoder/bin/mosesserver -f > /home/kamelnebhi/recaser/training/moses.ini --server-port 80 > Defined parameters (per moses.ini or switch): > config: /home/kamelnebhi/recaser/training/moses.ini > distortion-limit: 6 > feature: UnknownWordPenalty WordPenalty PhrasePenalty > PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 > path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0 > output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > input-factors: 0 > mapping: 0 T 0 > weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2 > TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5 > /home/kamelnebhi/mosesdecoder/bin > line=UnknownWordPenalty > FeatureFunction: UnknownWordPenalty0 start: 0 end: 0 > line=WordPenalty > FeatureFunction: WordPenalty0 start: 1 end: 1 > line=PhrasePenalty > FeatureFunction: PhrasePenalty0 start: 2 end: 2 > line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20 > num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz > input-factor=0 output-factor=0 > FeatureFunction: TranslationModel0 start: 3 end: 6 > line=Distortion > FeatureFunction: Distortion0 start: 7 end: 7 > line=KENLM lazyken=0 name=LM0 factor=0 > path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3 > FeatureFunction: LM0 start: 8 end: 8 > Loading the LM will be faster if you build a binary file. > Reading /home/kamelnebhi/recaser/training//cased.srilm.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > *The ARPA file is missing <unk>. Substituting log10 probability -100. > *************************************************************************************************** > Loading UnknownWordPenalty0 > Loading WordPenalty0 > Loading PhrasePenalty0 > Loading Distortion0 > Loading LM0 > Loading TranslationModel0 > Start loading text SCFG phrase table. Moses format : [3.69152] seconds > Reading /home/kamelnebhi/recaser/training/phrase-table.gz > ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 > **************************************************************************************************** > Segmentation fault (core dumped) > > *Thanks for your help* > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > http://mailman.mit.edu/mailman/private/moses-support/attachments/20140407/82302fab/attachment-0001.htm > > ------------------------------ > > Message: 2 > Date: Mon, 7 Apr 2014 16:00:47 -0400 > From: Philipp Koehn <[email protected] <mailto:[email protected]>> > Subject: Re: [Moses-support] Monolingual Word alignment > To: Mostafa Dehghani <[email protected] > <mailto:[email protected]>> > Cc: "[email protected] <mailto:[email protected]>" > <[email protected] <mailto:[email protected]>> > Message-ID: > > <CAAFADDBXoZv7=u5rqjay3brfwob92ywkrvfekdz6yrx29m7...@mail.gmail.com > <mailto:[email protected]>> > Content-Type: text/plain; charset=ISO-8859-1 > > Hi, > > this outcome is not that surprising to me. > > If you align identical sentences, then translating each word to itself > is a pretty good model. > > Since your goal is paraphrasing words into synonyms, you should > rather use methods such as the one proposed by Bannard and > Callison-Burch: http://acl.ldc.upenn.edu/P/P05/P05-1074.pdf > > -phi > > On Sun, Apr 6, 2014 at 11:11 AM, Mostafa Dehghani > <[email protected] <mailto:[email protected]>> wrote: > > Dear all, > > > > I am working on a method for Multilingual Information Retrieval. In my > > method I expand the text of each document by probabilistically > translating > > its words to other languages' words (interlingual expansion). > However, to > > pass some axioms, I need to expand text of each document in its own > language > > (intralingual expansion). So, beside bilingual word alignments, I need > > monolingual word alignments table (that probably contains the > alignment of > > each word to the words those are related/concurred with that word). > To do > > so, I used one side of each language sentences and their copy as > parallel > > corpus. Then I used the following command: > > > > > > train-model.perl -root-dir train -corpus corpus/fr-fr -f fr1 -e fr2 > > -alignment grow-diag-final-and -reordering msd-bidirectional-fe > > -external-bin-dir externalbin -last-step 4 > > > > > > such that fr-fr.fr1 fr-fr.fr2 are the same files containing French > > sentences. > > However, I got f2e and e2f files that are only contain alignments of > each > > word to itself with probability of 1. > > I am wondering is there any parameter that I should set to achieve words > > alignments (e2f/f2e) those are proper for intralingual expansion? > > > > Regards, > > > > -- > > Mostafa > > , > > > > http://khorshid.ut.ac.ir/~m.dehghani > <http://khorshid.ut.ac.ir/%7Em.dehghani> > > > > _______________________________________________ > > Moses-support mailing list > > [email protected] <mailto:[email protected]> > > http://mailman.mit.edu/mailman/listinfo/moses-support > > > > > ------------------------------ > > Message: 3 > Date: Mon, 7 Apr 2014 23:27:07 +0100 > From: Lucia Specia <[email protected] <mailto:[email protected]>> > Subject: [Moses-support] Call for Participation: Automatic and Manual > Metrics for Operational Translation Evaluation > To: [email protected] <mailto:[email protected]>, > [email protected] <mailto:[email protected]> > Message-ID: > > <caaleuxzvnsv0xp-uvxok0z8qwtkd-jt11ftoporho0ras9u...@mail.gmail.com > <mailto:caaleuxzvnsv0xp-uvxok0z8qwtkd-jt11ftoporho0ras9u...@mail.gmail.com>> > Content-Type: text/plain; charset="iso-8859-1" > > Dear all, > > This workshop may be relevant for those of you interested in MT evaluation > metrics. > > ---- > > Automatic and Manual Metrics for Operational Translation Evaluation > > http://mte2014.github.io/ > > 26 May 2014 > > Workshop at Language Resources and Evaluation Conference (LREC) 2014 > > http://lrec2014.lrec-conf.org > > In brief: > > We invite you to join us for an interesting day of work (and play!) as we > discuss metrics for machine translation quality assessment and participate > in some hands-on task-based translation evaluation. > > This workshop on Automatic and Manual Metrics for Operational Translation > Evaluation (MTE 2014) will be a full-day LREC workshop to be held on > Monday, May 26, 2014 in Reykjavik, Iceland. The format of MTE 2014 will be > interactive and energizing: a half-day of short presentations and > discussion of recent work on machine translation quality assessment, > followed by a half-day of hands-on collaborative work with MT metrics that > show promise for the prediction of task suitability of MT output. The > afternoon hands-on work will follow from the morning's presentations, with > some of the hands-on exercises developed directly from the submissions to > the workshop. > > Details: > > While a significant body of work has been done by the machine translation > (MT) research community towards the development and meta-evaluation of > automatic metrics to assess overall MT quality, less attention has been > dedicated to more operational evaluation metrics aimed at testing whether > translations are adequate within a specific context: purpose, end-user, > task, etc., and why the MT system fails in some cases. Both of these can > benefit from some form of manual analysis. Most work in this area is > limited to productivity tests (e.g. contrasting time for human translation > and MT post-editing). A few initiatives consider more detailed metrics for > the problem, which can also be used to understand and diagnose errors > in MT > systems. These include the Multidimensional Quality Metrics (MQM) recently > proposed by the EU F7 project QTLaunchPad, the TAUS Dynamic Quality > Framework, and past projects such as FEMTI, EAGLES and ISLE. Some of these > metrics are also applicable to human translation evaluation. A number of > task-based metrics have also been proposed for applications such as topic > ID / triage and reading comprehension. The purpose of this workshop is to > bring together representatives from academia, industry and government > institutions to discuss and assess metrics for manual and automatic > quality > evaluation, with an eye toward how they might be leveraged or further > developed into task-based metrics for more objective "fitness for purpose" > assessment. We will also consider comparisons to well-established metrics > for automatic evaluation such as BLEU, METEOR and others, including > reference-less metrics for quality prediction. The workshop will benefit > from datasets already collected and manually annotated for translation > errors by the QTLaunchPad project (http://www.qt21.eu/launchpad/) and will > cover concepts from many the metrics proposed by participants in the > half-day of hands-on tasks. > > Up-to-the-minute information and (most importantly) Registration: > > Additional details and schedule will be posted at the workshop website > http://mte2014.github.io/ as they become available. Register to attend via > the LREC registration site at > http://lrec2014.lrec-conf.org/en/registration/ > . > > We look forward to seeing you there! > > The MTE 2014 Organizing Committee > > Keith J. Miller (MITRE) > > Lucia Specia (University of Sheffield) > > Kim Harris (GALA and text & form) > > Stacey Bailey (MITRE) > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > http://mailman.mit.edu/mailman/private/moses-support/attachments/20140407/a8dbf5d0/attachment.htm > > ------------------------------ > > _______________________________________________ > Moses-support mailing list > [email protected] <mailto:[email protected]> > http://mailman.mit.edu/mailman/listinfo/moses-support > > > End of Moses-support Digest, Vol 90, Issue 19 > ********************************************* > > > > _______________________________________________ > Moses-support mailing list > [email protected] > http://mailman.mit.edu/mailman/listinfo/moses-support -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. _______________________________________________ Moses-support mailing list [email protected] http://mailman.mit.edu/mailman/listinfo/moses-support
