The following is a step-by-step instruction to do INDRA treebanking:

1. Make a testsuite

General guidelines and formatting: http://compling.hss.ntu.edu.sg/courses/hg7021/testsuites.html

2. The testsuite should be placed in ~/ind/tsdb/skeletons

3. Add testsuite information in ~/ind/tsdb/skeletons/index.lisp

At the end of index.lisp: ((:path . “nameoftestsuite”) (:content . “explanation”))

4. Make a shortcut of ind folder in ~/logon/ntu

5. Make a shortcut of skeletons folder in ~/logon/lingo/lkb/src/tsdb/skeletons

Rename that folder into ind

6. Make sure that the paths for ind skeletons etc. are in these files:

~/logon/bin/answer
~/logon/dot.tsdbrc
~/logon/parse

7. Run this command in logon$

~/logon$ ./parse --binary --ind --protocol 2 --best 1 --limit 0 --count 8 mrs

8 is the number of CPU. It can be checked in System Monitor.
mrs is the name of testsuite folder.

8. Run [incr tsdb()]

Database: Home/logon/lingo/lkb/src/tsdb/home/ind
Skeleton: Home/logon/lingo/lkb/src/tsdb/skeletons/ind

See GeFaqTsdbRc to make changes to the default Database and Skeleton paths

9. Activate external treebanking tool

Trees > Switches > External Treebanking Tool

10. To automatically update:

Compare > Source Database and choose a previously annotated file

then

Trees > Update : Automatic Update

11. To annotate:

Trees > Annotate

The profile will be saved in ~/logon/lingo/lkb/src/tsdb/home/ind/

Treebanking with ACE

Based on CapitolHillTreebank

1. Compile the grammar

~/grammar/ind$ ace -g ace/config.tdl -G ind.dat

Check by parsing sentences

~/grammar/ind$ ace -g ind.dat -l

2. Step-by-step command line to FFTB

(1)

~/grammar/ind$ mkprof -s tsdb/skeletons/(name of testsuite) /tmp/(name of testsuite)-demo

(2)

without YY mode (for unknown word handling):

~/grammar/ind$ art -f -a 'ace --disable-generalization -g ind.dat -O' /tmp/(name of testsuite)-demo/

with YY mode (for unknown word handling):

~/grammar/ind$ art -f -Ya './yy.sh | ace --disable-generalization -g ind.dat -O -y' /tmp/(name of testsuite)-demo/

~/grammar/ind$ vi /tmp/(name of testsuite)-demo/edge

(3)

~/grammar/ind$ fftb -g ind.dat --browser --webdir=$LOGONROOT/lingo/answer/fftb /tmp/(name of testsuite)-demo/

Save the result to the gold folder and update

~/grammar/ind$ fftb -g ind.dat /tmp/(name of testsuite)-demo/ --browser --gold tsdb/gold/(name of testsuite)

Feature Forest-based Maximum Entropy Model Trainer

1. Download fftrain-0.9.25-linux-x86.tar.gz from http://sweaglesw.org/linguistics/

2. Extract and put the folder fftrain-0.9.25 into any folder

3. Command lines (e.g. mrs gold profile), choose a name e.g. mrs-ff:

~/grammar/ind$ mkprof -s tsdb/gold/mrs mrs-ff
~/grammar/ind$ art -a "ace -g ind.dat -O" -f mrs-ff
~/grammar/ind$ FFGRANDPARENT=0 ~/tools/fftrain-0.9.25/ffmaster 1 mrs-gp0.mem &
~/grammar/ind$ FFGRANDPARENT=0 ~/tools/fftrain-0.9.25/ffworker ind.dat mrs-ff tsdb/gold/mrs localhost

Try parsing a sentence:

~/grammar/ind$ echo "Kucing mengejar anjing." | ace -g ind.dat -1Tf --maxent=mrs-gp0.mem

~/grammar/ind$ ace -g ind.dat -1Tf --maxent=mrs-gp0.mem -l

Make a new profile based on the Maximum Entropy Model Trainer

~/grammar/ind$ mkprof -s tsdb/skeletons/mrs /tmp/mrs-demo
~/grammar/ind$ art -a 'ace -g ind.dat --maxent=mrs-gp0.mem' /tmp/mrs-demo/
~/grammar/ind$ ~/tools/fftrain-0.9.25/mrs-scorer-linux-x86.static ~/grammar/ind/tsdb/gold/mrs /tmp/mrs-demo

Last update: 2018-10-10 by DavidMoeljadi [edit]