threads error in running stanford LLDA tmt scala models -

When I run the Stanford LLDA TMT scale model, I have to face some problems. One of them is a thread error when I try to conclude with the LLDA TMT model. The code I am running is actually provided by Shreyas Karnik in the sourcefork link,

@Sarab: Here are links to code: bit bit.ly/ocK2T9 (education) and bit. Ly / qIWb6C (Conclusion) Please tell me if you still face any errors.

The error message is,

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The command started: Venus 21 21:34:48 CDT 2013 Java-Dascalanlp.distributed.hub = socket: //crick7.mayo. edu: 41080 / hub -Dscalanlp.distributed.id = / tmt / 0 -Xmx100000m edu.stanford.nlp.tmt.TMTMain "/ data4 / bsi /nlp/s110067.sharp/bioask/tmtModels/example-7-llda-infer .scala "

Loading model ...

  TSVFile (" test.csv ") ~ & gt; IDC column (1) ~> Columns (2) ~ & gt; Output is generated ... [concurrent] 128 permits [concurrent [synchronic]] 128 permits  
  exception in thread "thread -3" java.lang.IndexOfBoundsException: 1 scala.collection. LinearSeqOptimized $ class.apply (LinearSeqOptimized.scala: 51) at scala.collection. Unchanging.Li. (List Scala: 45) Scalanclip.Stage. Column.map (column selectors scala: 51) ScalancelP.Stage. Colmkmap (Column Selectors. Skla: 46) Skelanlpikstej. GenerickMapper $ $ $ Anonfun $ 1 apply $ $ Apply $ $ $ 2kapply (Mapper on. Scala: 36) ScalanlpkstagekItem. (Item.scala: 32) scalanlp.stage.generic.Mapper $ $ anonfun $ $$ apply to the map .apply (mapper scala: 36) scalanlp.stage.generic.Mapper $ $ nonprofit $ $ 1.apply (mapper.scala: 36) on scala.collection.Iterator $ $ anon $ 19.next (Iterator.scala: 335)) Scala.collection.Iterator $ $ anon edu at $ 19.next (Iterator.scala: 335). on stanford.nlp.tmt.data.concurrent.Concurrent $$ Anonfun $ map $ 2.apply (concurrent.scala: 96) at edu.stanford.nlp.tmt.data.concurrent.Concurrent $$ anonfun $ map $ 2. apply (Concurrent.scala: 88) at edu.stanford.nlp.tmt .data.concurrent.Concurrent $$ anon $ 4.run (concurrent.scala: 45)   
 a Or will you give support? Very much appreciate!   
 
 
 This is a known issue of TMT 0.4.0 for many users. TMT-0.2.2 just works fine. But support for TMT-0.4.0 has been discontinued and earlier it has been supported for TMT-3.0.2. You can check out, in which the GUI is also available as easy as it is.