Difference between revisions of "Lexical selection"

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[[Sélection lexicale|En français]]

{{TOCD}}
{{TOCD}}
'''Lexical selection''' is the task of choosing, given several source-language (SL) translations with the same part-of-speech (POS), the most adequate translation among them in the target language (TL). The task is related to the task of [[word-sense disambiguation]]. The difference is that its aim is to find the most adequate translation, not the most adequate sense. Thus, it is not necessary to choose between a series of fine-grained senses if all these senses result in the same final translation.
'''Lexical selection''' is the task of choosing, given several source-language (SL) translations with the same part-of-speech (POS), the most adequate translation among them in the target language (TL). The task is related to the task of [[word-sense disambiguation]]. The difference is that its aim is to find the most adequate translation, not the most adequate sense. Thus, it is not necessary to choose between a series of fine-grained senses if all these senses result in the same final translation.
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* [[Word sense disambiguation]]
* [[Word sense disambiguation]]


== Current lexical selection module (2012) ==
== Current lexical selection module (2012–current) ==


This is made by [Francis Tyers] an is deployed in XX-XX language pair where you can see an example.
The [[Constraint-based lexical selection module]] / apertium-lex-tools is made by [[User:Francis Tyers|Francis Tyers]] and is deployed in the apertium-sh-mk and apertium-kaz-tat language pairs where you can see an example.


This uses a module which runs ''after'' bidix, where the bidix output is ambiguous:
<pre>
morf.analysis | morf.disambiguation | bidix | lexical selection | structural transfer | morf. generation
</pre>
In a sense, it disambiguates the bidix output (in exactly the same way that morf.disambiguation disambiguates the morf.analysis output).

Some documentation:
* [[Rule-based lexical selection module]]
* [[Rule-based lexical selection module]]
* [[Generating lexical-selection rules from a parallel corpus]]
* [[Learning rules from parallel and non-parallel corpora]]
* [[How to get started with lexical selection rules]]
* [[How to get started with lexical selection rules]]
** [[Как начать работу с правилами по выбору лексики]]
** [[Как начать работу с правилами по выбору лексики]]


== Old and alternative approaches ==
== The slr/srl approach (2010-2012) ==

=== The slr/srl + CG approach (2010-2012) ===
This was used in [[apertium-sme-nob]] until lately.


This uses a special [[Constraint Grammar]] (CG) file which runs ''after'' regular morphological disambiguation, but ''before'' bidix:
This uses a special [[Constraint Grammar]] (CG) file which runs ''after'' regular morphological disambiguation, but ''before'' bidix:
<pre>
<pre>
morf.analysis | morf.disambiguation (cg or apertium-tagger) | cg lexical selection | bidix | transfer | morf. generation
morf.analysis | morf.disambiguation (cg or apertium-tagger) | cg lexical selection | bidix | structural transfer | morf. generation
</pre>
</pre>


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* pairs which only want lex.sel require the user to install vislcg3
* pairs which only want lex.sel require the user to install vislcg3
* developers need to remember when they write the rules that number 1 was "og at" and number 0 was "at", which can get confusing (especially if you decide to change the default) – more points of failure.
* developers need to remember when they write the rules that number 1 was "og at" and number 0 was "at", which can get confusing (especially if you decide to change the default) – more points of failure.
** On the other hand side, lexical selection can most often be seen as a / default - special case / dichotomy. A good mode of work is to introduce each rule set with the number array, e.g.: # leat 0 = være, 1 = ha, 2 = måtte («ha å»)


apertium-sme-nob in 2014 switched to bidix before lex.sel (like the lrx-proc method), but still uses vislcg3 rules instead of lrx-proc.
== Transfer rule approach (2009) ==

=== Transfer rule approach (2009) ===


You can make transfer rules that does lexical selection.
You can make transfer rules that does lexical selection.
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* must write rules
* must write rules


This is the method used in most pairs.
This is the method used in most trunk pairs.

=== Lextor (2007) ===

[[Lextor]] works using statistics and requires 1) slightly pre-processed dictionaries and 2) corpora to train the module. '''The module is turned off in most cases as it does not provide an improvement over the baseline.'''


== Deprecated (2007) ==


* [[Lextor]]
* [[Lexical selection in target language]]
* [[Limited rule-based lexical selection]]
* [[Generating lexical-selection rules]]





Latest revision as of 08:36, 29 April 2015

En français

Lexical selection is the task of choosing, given several source-language (SL) translations with the same part-of-speech (POS), the most adequate translation among them in the target language (TL). The task is related to the task of word-sense disambiguation. The difference is that its aim is to find the most adequate translation, not the most adequate sense. Thus, it is not necessary to choose between a series of fine-grained senses if all these senses result in the same final translation.

This page has some links to pages about lexical selection in Apertium.

General information:

Current lexical selection module (2012–current)[edit]

The Constraint-based lexical selection module / apertium-lex-tools is made by Francis Tyers and is deployed in the apertium-sh-mk and apertium-kaz-tat language pairs where you can see an example.

This uses a module which runs after bidix, where the bidix output is ambiguous:

morf.analysis | morf.disambiguation | bidix | lexical selection | structural transfer | morf. generation

In a sense, it disambiguates the bidix output (in exactly the same way that morf.disambiguation disambiguates the morf.analysis output).

Some documentation:

Old and alternative approaches[edit]

The slr/srl + CG approach (2010-2012)[edit]

This was used in apertium-sme-nob until lately.

This uses a special Constraint Grammar (CG) file which runs after regular morphological disambiguation, but before bidix:

morf.analysis | morf.disambiguation (cg or apertium-tagger) | cg lexical selection | bidix | structural transfer | morf. generation

The CG rules add a number to the lemma of the word if we want a non-default translation, so ^ahte<CC>$ might turn into ^ahte:1<CC>$.

The bidix has entries like

<e>            <p><l>ahte<s n="CC"/></l><r>at<s n="cnjcoo"/><s n="clb"/></r></p></e>
<e slr="1"><p><l>ahte<s n="CC"/></l><r>og<b/>at<s n="cnjcoo"/><s n="clb"/></r></p></e>

This is pre-processed by an XSLT script, so the file that is given to lt-comp actually contains

<e>            <p><l>ahte<s n="CC"/></l><r>at<s n="cnjcoo"/><s n="clb"/></r></p></e>
<e R="lr"><p><l>ahte:1<s n="CC"/></l><r>og<b/>at<s n="cnjcoo"/><s n="clb"/></r></p></e>

So if the CG rule fired, and turned ahte into ahte:1, we get "og at" instead of "at".


Downsides with this approach:

  • pairs which only want lex.sel require the user to install vislcg3
  • developers need to remember when they write the rules that number 1 was "og at" and number 0 was "at", which can get confusing (especially if you decide to change the default) – more points of failure.
    • On the other hand side, lexical selection can most often be seen as a / default - special case / dichotomy. A good mode of work is to introduce each rule set with the number array, e.g.: # leat 0 = være, 1 = ha, 2 = måtte («ha å»)

apertium-sme-nob in 2014 switched to bidix before lex.sel (like the lrx-proc method), but still uses vislcg3 rules instead of lrx-proc.

Transfer rule approach (2009)[edit]

You can make transfer rules that does lexical selection. Its not very elegant but it works, to a degree. The drawback is that you:

  • get big transfer files
  • mix transfer and lexical selection
  • must write rules

This is the method used in most trunk pairs.

Lextor (2007)[edit]

Lextor works using statistics and requires 1) slightly pre-processed dictionaries and 2) corpora to train the module. The module is turned off in most cases as it does not provide an improvement over the baseline.