Constraint-based lexical selection module

apertium-lex-tools provides a module for compiling lexical selection rules and processing them in the pipeline. Rules can be manually written, or learnt from monolingual or parallel corpora.

Installing

Prerequisites and compilation are the same as lttoolbox and apertium, as well as (on Debian/Ubuntu) zlib1g-dev.

See Installation, for most real operating systems you can now get pre-built packages of apertium-lex-tools (as well as other core tools) through your regular package manager.

Lexical transfer in the pipeline

lrx-proc runs between bidix lookup and the first stage of transfer, e.g.

… apertium-pretransfer | lt-proc -b kaz-tat.autobil.bin | lrx-proc kaz-tat.lrx.bin \
  | apertium-transfer -b apertium-kaz-tat.kaz-tat.t1x  kaz-tat.t1x.bin | …

This is the output of lt-proc -b on an ambiguous bilingual dictionary:

[74306] ^El<det><def><f><sg>/The<det><def><f><sg>$ 
^estació<n><f><sg>/season<n><sg>/station<n><sg>$ ^més<preadv>/more<preadv>$ 
^plujós<adj><f><sg>/rainy<adj><sint><f><sg>$ 
^ser<vbser><pri><p3><sg>/be<vbser><pri><p3><sg>$ 
^el<det><def><f><sg>/the<det><def><f><sg>$ 
^tardor<n><f><sg>/autumn<n><sg>/fall<n><sg>$^,<cm>/,<cm>$ 
^i<cnjcoo>/and<cnjcoo>$ ^el<det><def><f><sg>/the<det><def><f><sg>$ 
^més<preadv>/more<preadv>$ ^sec<adj><f><sg>/dry<adj><sint><f><sg>$ 
^el<det><def><m><sg>/the<det><def><m><sg>$ 
^estiu<n><m><sg>/summer<n><sg>$^.<sent>/.<sent>$

I.e.

L'estació més plujosa és la tardor, i la més seca l'estiu

Goes to:

The season/station more rainy is the autumn/fall, and the more dry the summer.

Apertium/lttoolbox 3.3 and onwards support the -b option to lt-proc / apertium-transfer.

Usage

Make a simple rule file,

<rules>
  <rule>
    <match lemma="criminal" tags="adj"/>
    <match lemma="court" tags="n.*"><select lemma="juzgado" tags="n.*"/></match>
  </rule>
</rules>

Then compile it:

$ lrx-comp rules.xml rules.fst
1: 32@32

The input is the output of lt-proc -b,

$ echo "^There<adv>/Allí<adv>$ ^be<vbser><pri><p3><sg>/ser<vbser><pri><p3><sg>$ ^a<det><ind><sg>/uno<det><ind><GD><sg>$ 
^criminal<adj>/criminal<adj><mf>/delictivo<adj>$ 
^court<n><sg>/corte<n><f><sg>/cancha<n><f><sg>/juzgado<n><m><sg>/tribunal<n><m><sg>$^.<sent>/.<sent>$" | ./lrx-proc -t rules.fst 
1:SELECT<1>:court<n><sg>:<select>juzgado<n><ANY_TAG>
^There<adv>/Allí<adv>$ ^be<vbser><pri><p3><sg>/ser<vbser><pri><p3><sg>$ ^a<det><ind><sg>/uno<det><ind><GD><sg>$ 
^criminal<adj>/criminal<adj><mf>/delictivo<adj>$ ^court<n><sg>/juzgado<n><m><sg>$^.<sent>/.<sent>$

Rule format

A rule is made up of an ordered list of:

• Matches
• Operations (select, remove)

<rule>  
  <match lemma="el"/>  
  <match lemma="dona" tags="n.*">    
    <select lemma="wife"/> 
  </match>  
  <match lemma="de"/>
</rule>

<rule>  
  <match lemma="estació" tags="n.*">    
    <select lemma="season"/> 
  </match>  
  <match lemma="més"/>
  <match lemma="plujós"/>
</rule>

<rule>  
  <match lemma="guanyador"/>
  <match lemma="de"/>
  <match/>
  <match lemma="prova" tags="n.*">    
    <select lemma="event"/> 
  </match>  
</rule>

Weights

The rules compete with each other. That is why a weight is assigned to each of them. In the case of a word that has several possible translations in the dictionary, all rules are evaluated. For each possible translation, the weights of the rules that match the context of the use of the word in the sentence are added up, and the translation with the highest value is chosen. For instance, let's consider these two rules:

  <rule weight="0.8">
    <match lemma="ferotge" tags="adj.*"><select lemma="farouche"/></match>
  </rule>
  <rule weight="1.0">
    <or>
      <match lemma="animal" tags="n.*"/>
      <match lemma="animau" tags="n.*"/>
    </or>
    <match lemma="ferotge" tags="adj.*"><select lemma="féroce"/></match>
  </rule>

If we have "un animal ferotge", the translation "farouche" will get 0.8 points, and "féroce" will get 1.0. The latter will be chosen.

Special cases

Matching a capitalized word

Below, the noun "audiència" will be usually translated as "audience", but if it is written as "Audiència", "cour# d'assises" (i.e. cour<g><b/>d'assises</g>) will be elected:

  <rule weight="0.8">
    <match lemma="audiència" tags="n.*"><select lemma="audience"/></match>
  </rule>
  <rule weight="1.0">
    <match lemma="Audiència" tags="n.*"><select lemma="cour# d'assises"/></match>
  </rule>

Matching an unknown word

Below, the noun "mossèn" will be usually translated as "curé", but if it is followed by an anthroponym (rule 2) or an unknown word (rule 3), "monseigneur" will be elected:

  <rule weight="0.8">
    <match lemma="mossèn" tags="n.*"><select lemma="curé"/></match>
  </rule>
  <rule weight="1.0">
    <match lemma="mossèn" tags="n.m.sg"><select lemma="monseigneur"/></match>
    <match tags="np.ant.*"/>
  </rule>
  <rule weight="1.0">
    <match lemma="mossèn" tags="n.m.sg"><select lemma="monseigneur"/></match>
    <match tags=""/>
  </rule>

Writing and generating rules

Writing

Main article: How to get started with lexical selection rules

A good way to start writing lexical selection rules is to take a corpus, and search for the problem word, you can then look at how the word should be translated, and the contexts it appears in.

Generating

Parallel corpus

Main article: Learning rules from parallel and non-parallel corpora

Monolingual corpora

Main article: Running_the_monolingual_rule_learning

Todo and bugs

• xml compiler
• compile rule operation patterns, as well as matching patterns
• make rules with gaps work
• optimal coverage
• fix bug with processing multiple sentences
• instead of having regex OR, insert separate paths/states.
• optimise the bestPath function (don't use strings to store the paths)
• autotoolsise build
• add option to compiler to spit out ATT transducers
• fix bug with outputting an extra '\n' at the end
• edit transfer.cc to allow input from lt-proc -b
• profiling and speed up
  • why do the regex transducers have to be minimised ?
  • retrieve vector of strings corresponding to paths, instead of a single string corresponding to all of the paths
  • stop using string processing to retrieve rule numbers
  • retrieve vector of vectors of words, not string of words from lttoolbox
  • why does the performance drop substantially with more rules ?
  • add a pattern -> first letter map so we don't have to call recognise() with every transition (didn't work so well)
• there is a problem with the regex recognition code: see bug1 in testing.
• there is a problem with two defaults next to each other; bug2 in testing.
• default to case insensitive ? (perhaps case insensitive for lower case, case sensitive for uppercase) -- see bug4 in testing/.
• make sure that -b works with -n too.
• testing
• null flush
• add option to processor to spit out ATT transducers
• use brown clusters to merge rules with the same context, or remove parts of context from rules which are not relevant?
• https://sourceforge.net/p/apertium/tickets/64/ <match tags="n.*"></match> never matches, while <match tags="n.*"/> does

Rendimiento

• 2011-12-12: 10,000 words / 97 seconds = 103 words/sec (71290 words, 14.84 sec = 4803 words/sec)
• 2011-12-19: 10,000 words / 4 seconds = 2,035 words/sec (71290 words, 8 secs = 8911 words/sec)

Preparedness of language pairs

Pair	LR (L)	LR (L→R)	Fertility	Rules
apertium-is-en	18,563	22,220	1.19	115
apertium-es-fr
apertium-eu-es	16,946	18,550	1.09	250
apertium-eu-en
apertium-br-fr	20,489	20,770	1.01	256
apertium-mk-en	8,568	10,624	1.24	81
apertium-es-pt
apertium-es-it
apertium-es-ro
apertium-en-es	267,469	268,522	1.003	334
apertium-en-ca

Troubleshooting

If you get the message lrx-comp: error while loading shared libraries: libapertium3-3.2.so.0: cannot open shared object file: No such file or directory you may need to put this in your ~/.bashrc

LD_LIBRARY_PATH="/usr/local/lib:$LD_LIBRARY_PATH"

Then open a new terminal before using lrx-comp/lrx-proc.

On a 64-bit machine, apertium-lex-tools make may fail because the zlib is missing, even though you have zlib1g-dev installed. If you get the error message /usr/bin/ld: cannot find -lz, do the following: install package lib32z1-dev (which will install many other dependencies), even though it is a 32-bit binary, it is needed to compile the sources.

See also

• How to get started with lexical selection rules
• SVN Module: apertium-lex-tools

References

• Tyers, F. M., Sánchez-Martínez, F., Forcada, M. L. (2012) "Flexible finite-state lexical selection for rule-based machine translation". Proceedings of the 17th Annual Conference of the European Association of Machine Translation, EAMT12
• Tyers et al Feasible lexical selection for rule-based machine translation
• Tyers et al Unsupervised training of maximum-entropy models for lexical selection in rule-based machine translation