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Re: [ACTION-94]: go and find examples of concept ontology (semantic features of terms as opposed to domain type ontologies)

From: Tadej Stajner <tadej.stajner@ijs.si>
Date: Thu, 07 Jun 2012 16:06:06 +0200
Message-ID: <4FD0B54E.7000208@ijs.si>
To: public-multilingualweb-lt@w3.org
Hi Felix,
as far as I'm aware, URIs only exist for the English wordnet. Maybe 
prefixing the a # was not the best stylistic choice here, but yes, what 
I meant to convey is that that value was a local identifier, valid 
within a particular semantic network.

In the ideal scenario, these selectors would be dereferencible and 
verifiable via URIs for arbitrary wordnets and terminology lexicons and 
their entries. Do we have any people involved in developing semantic 
networks or term lexicons on this list? The compromise is allowing some 
limited classes of non-URI local selectors, like synset IDs for 
wordnets, and term IDs for TBX lexicons.

-- Tadej

On 6/7/2012 3:44 PM, Felix Sasaki wrote:
> Thanks, Tadej.
>
> The value of the its-selector attribute looks like a document internal 
> link. But it is probably an identifier of the synset in the given 
> semantic network, no?
>
> About 1) and 2): is your made-up example then the output of the text 
> annotation use case? I am asking since you say "2) markup in raw ITS", 
> so I'm not sure.
>
> Also, it seems that an implementation needs to "know" about the 
> resources that are identified via its-semantic-network-ref. This is 
> really an identifier, like
> http://www.w3.org/2005/xpath-functions/collation/codepoint/
> is an identifier for a Unicode code point collation; it doesn't give 
> you the collation data, but creating an implementation that 
> "understands" the identifier means probably caching the collation 
> data. The same would be true for the semantic network.
>
> This leads to the next question: can we engage the developers of the 
> semantic network (or other disambiguation related) resources to come 
> up with stable URIs for these? It would be great to list these URIs in 
> our specification and say "this is how you identify the English 
> wordnet etc.", for scenarios like the collation data mentioned above.
>
> Felix
>
> 2012/6/7 Tadej Štajner <tadej.stajner@ijs.si 
> <mailto:tadej.stajner@ijs.si>>
>
>     Hi,
>
>     I agree with Pedro on the questions. Automatic word sense
>     disambiguation is in practice still not perfect, so some
>     semi-automatic user interfaces make a lot of sense. And how I
>     think that this could look like in a made-up example, answering
>     Felix's 1) and 2):
>
>     1) HTML+ITS: <span its-disambiguation
>     its-semantic-network-ref="http://www.sfs.uni-tuebingen.de/lsd/index.shtml"
>     <http://www.sfs.uni-tuebingen.de/lsd/index.shtml>
>     its-selector="#synset_loschen_3">löschen</span>
>
>     2) Markup in raw ITS
>     <its:disambiguation
>        
>     semanticNetworkRef="http://www.sfs.uni-tuebingen.de/lsd/index.shtml"
>     <http://www.sfs.uni-tuebingen.de/lsd/index.shtml>
>         selector="#synset_loschen_3">löschen</its:disambiguation>
>
>     -- Tadej
>
>
>
>     On 04. 06. 2012 13 <tel:04.%2006.%202012%2013>:53, Pedro L. Díez
>     Orzas wrote:
>>
>>     Dear Felix,
>>
>>     Thank you very much. Probably Tadej can prepare the use cases you
>>     mention, with the consolidated data category. About the question
>>     3 and 4, I can tell you the following:
>>
>>     3) Would it be produced also by an automatic text annotation tool?
>>
>>     For the pointers to the three information referred (concepts in
>>     Ontology, meanings in Lexical DB, and terms in Terminological
>>     resources) I think it would be possible semiautomatic annotation
>>     tools, that is, proposed by the tool and confirmed by user.
>>
>>     The fully automatic text annotation  would need more sophisticate
>>     “semantic calculus”, and most of these are under research, as far
>>     as I know. Maybe, in this cases, it should be combined with
>>     textAnalysisAnnotation, specifying in *Annotation agent* – and
>>     *Confidence score* – which systemand with which reliability has
>>     been produced.
>>
>>     4) Would 1-2 be consumed by an MT tool, or by other tools?
>>
>>     These can be basically consumed by language processing tools,
>>     like MT, and other Linguistic Technology that needs content or
>>     semantic info. For instance Text Analytics, Semantic search,
>>     etc.. In the localization chains, these information can be also
>>     used by automatic or semiautomatic processes (like selection of
>>     dictionaries for translations, or selection of
>>     translators/revisers by subject area)
>>
>>     It could be also used by humans for translation or post-edition
>>     in case of ambiguity or lake of context in the content, but
>>     mostly by automatic systems.
>>
>>     I hope this helps.
>>
>>     Pedro
>>
>>     ------------------------------------------------------------------------
>>
>>     *De:*Felix Sasaki [mailto:fsasaki@w3.org]
>>     *Enviado el:* sábado, 02 de junio de 2012 14:13
>>     *Para:* Tadej Stajner; pedro.diez
>>     *CC:* public-multilingualweb-lt@w3.org
>>     <mailto:public-multilingualweb-lt@w3.org>
>>     *Asunto:* Re: [ACTION-94]: go and find examples of concept
>>     ontology (semantic features of terms as opposed to domain type
>>     ontologies)
>>
>>     Hi Tadej, Pedro, all,
>>
>>     this looks like a great chain of producing and consuming metadata.
>>
>>     Apologies if this was explained during last weeks call or before,
>>     but can you clarify a bit the following:
>>
>>     1) How would the actual HTML markup produced in the original text
>>     annotation use case look like?
>>
>>     2) How would the markup in this use case look like?
>>
>>     3) Would it be produced also by an automatic text annotation tool?
>>
>>     4) Would 1-2 be consumed by an MT tool, or by other tools?
>>
>>     Thanks again,
>>
>>     Felix
>>
>>     2012/5/31 Tadej Stajner <tadej.stajner@ijs.si
>>     <mailto:tadej.stajner@ijs.si>>
>>
>>     Hi Pedro,
>>     thanks for the excellent explanation. If I understand you
>>     correctly, a sufficient example for this use case would be
>>     annotation of individual words with synset URI of the appropriate
>>     wordnet? If so, then I believe this route can be practical - I
>>     think linking to the synset is a more practical idea than
>>     expressing semantic features of the word given the available tools.
>>
>>     Enrycher can do automatic all-word disambiguation into the
>>     english wordnet, whereas  we don't have anything specific in
>>     place for semantic features (which I suspect also holds for other
>>     text analytics providers).
>>
>>     I'm also in favor of prescribing wordnets for individual
>>     languages as valid selector domains as you suggest in option 1).
>>     That would make validation easier since we have a known domain.
>>
>>     @All: Can we come up with a second implementation for this use
>>     case, preferrably a consumer?
>>
>>     -- Tadej
>>
>>
>>
>>
>>     On 5/29/2012 2:00 PM, Pedro L. Díez Orzas wrote:
>>
>>     Dear all,
>>
>>     Sorry for the delay. I tried to contact some people I think can
>>     contribute to this, but they are not available these weeks.
>>
>>     Before providing an example to consider all if it is worthwhile
>>     to maintain “semantic selector” attribute in the consolidation of
>>     “Disambiguation” I would like to do a couple considerations:
>>
>>      1. Probably we will not have short term any implementation, but
>>         there are for example few semantic networks available in web
>>         (see http://www.globalwordnet.org/gwa/wordnet_table.html)
>>         that could be mapped using semantic selectors. See on line
>>         for example, the famous http://wordnetweb.princeton.edu
>>         <http://wordnetweb.princeton.edu/perl/webwn>).
>>      2. The W3C working group SKOS (Simple Knowledge Organization
>>         System Reference) are maybe dealing with similar things.
>>
>>     The “semántica selector” allows further lexical (simple words or
>>     multi words) distinctions than a “domain” or an ontology like
>>     NERD. Also, the denotation is different from the “concept
>>     reference”, most of all in part of speech like verbs.
>>
>>     Within the same domain, referring to very similar concepts,
>>     languages have semantic differences. Depending on the semantic
>>     theory used, each tries to captivate these differences by means
>>     of different systems (semantic features, semantic primitives,
>>     semantic nodes (in semantic networks), other semantic
>>     representations). An example could be the German verb “löschen”,
>>     which in different contexts can take different meanings that can
>>     be try to capture using different selectors, with the different
>>     systems.
>>
>>     –löschen                        -> clear             (some bits)
>>                                        -> delete           (files)
>>                                        -> cancel          (programs)
>>                                        -> erase            (a scratchpad)
>>                                        -> extinguish     (a fire)
>>
>>     Other possible translations of the verb**“löschen” are:
>>
>>     delete
>>
>>     	
>>
>>     löschen, streichen, tilgen, ausstreichen, herausstreichen
>>
>>     clear
>>
>>     	
>>
>>     löschen, klären, klarmachen, leeren, räumen, säubern
>>
>>     erase
>>
>>     	
>>
>>     löschen, auslöschen, tilgen, ausradieren, radieren, abwischen
>>
>>     extinguish
>>
>>     	
>>
>>     löschen, auslöschen, zerstören
>>
>>     quench
>>
>>     	
>>
>>     löschen, stillen, abschrecken, dämpfen
>>
>>     put out
>>
>>     	
>>
>>     löschen, bringen, ausmachen, ausschalten, treiben, verstimmen
>>
>>     unload
>>
>>     	
>>
>>     entladen, abladen, ausladen, löschen, abstoßen, abwälzen
>>
>>     discharge
>>
>>     	
>>
>>     entladen, erfüllen, entlassen, entlasten, löschen, ausstoßen
>>
>>     wipe out
>>
>>     	
>>
>>     auslöschen, löschen, ausrotten, tilgen, zunichte machen, auswischen
>>
>>     slake
>>
>>     	
>>
>>     stillen, löschen
>>
>>     close
>>
>>     	
>>
>>     schließen, verschließen, abschließen, sperren, zumachen, löschen
>>
>>     blot
>>
>>     	
>>
>>     löschen, abtupfen, klecksen, beklecksen, sich unmöglich machen,
>>     sich verderben
>>
>>     turn off
>>
>>     	
>>
>>     ausschalten, abbiegen, abstellen, abdrehen, einbiegen, löschen
>>
>>     blow out
>>
>>     	
>>
>>     auspusten, löschen, aufblasen, aufblähen, aufbauschen, platzen
>>
>>     zap
>>
>>     	
>>
>>     abknallen, düsen, umschalten, löschen, töten, kaputtmachen
>>
>>     redeem
>>
>>     	
>>
>>     einlösen, erlösen, zurückkaufen, tilgen, retten, löschen
>>
>>     pay off
>>
>>     	
>>
>>     auszahlen, bezahlen, tilgen, abzahlen, abbezahlen, löschen
>>
>>     switch out
>>
>>     	
>>
>>     löschen
>>
>>     unship
>>
>>     	
>>
>>     ausladen, entladen, abnehmen, löschen
>>
>>     souse
>>
>>     	
>>
>>     eintauchen, durchtränken, löschen, nass machen
>>
>>     rub off
>>
>>     	
>>
>>     abreiben, abgehen, abwetzen, ausradieren, abscheuern, löschen
>>
>>     strike off
>>
>>     	
>>
>>     löschen
>>
>>     land
>>
>>     	
>>
>>     landen, an Land gehen, kriegen, an Land ziehen, aufsetzen, löschen
>>
>>     According to this, the consolidation of
>>     disambiguation/namedEntity/  data categories under “Terminology”
>>     http://www.w3.org/International/multilingualweb/lt/wiki/Requirements#disambiguation
>>     could be the following. It is thought to cover operational URI or
>>     XPath pointers to the current three most important semantic
>>     resources: conceptual (ontology), semantic (semantic networks or
>>     lexical databases) and terminological (glossaries and
>>     terminological resources), where ontologies are used for both
>>     general lexicon and terminology, semantic networks to represent
>>     general vocabulary (lexicon), and terminological resources
>>     specialized vocabulary.
>>
>>     *disambiguation*
>>
>>     Includes data to be used by MT systems in disambiguating
>>     difficult content
>>
>>     *Data model*
>>
>>       * concept reference: points to a *concept in an ontology* that
>>         this fragment of text represents. May be an URI or an XPath
>>         pointer.
>>       * semantic selector: points to a *meaning in an semantic
>>         network* that this fragment of text represents. May be an URI
>>         or an XPath pointer.
>>       * terminology reference: points to *a term in a terminological
>>         resource* that this fragment of text represents. May be an
>>         URI or an XPath pointer.
>>       * equivalent translation: expressions of that concept in other
>>         languages, for example for training MT systems
>>
>>     Also, I would keep *textAnalysisAnnotation*, since the purpose is
>>     quite different.
>>
>>     Anyway, if we consider not to include “semantic selector” now,
>>     maybe it can be for future versions or to be treated in liaison
>>     with other groups.
>>
>>     I hope it helps,
>>
>>     Pedro
>>
>>     *__________________________________*
>>
>>     **
>>
>>     *Pedro L. Díez Orzas*
>>
>>     *Presidente Ejecutivo/CEO*
>>
>>     *Linguaserve Internacionalización de Servicios, S.A.*
>>
>>     *Tel.: +34 91 761 64 60 <tel:%2B34%2091%20761%2064%2060>
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>>
>>     *E-mail: **pedro.diez@linguaserve.com
>>     <mailto:pedro.diez@linguaserve.com>*
>>
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>>
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>>
>>     -- 
>>     Felix Sasaki
>>
>>     DFKI / W3C Fellow
>>
>
>
>
>
> -- 
> Felix Sasaki
> DFKI / W3C Fellow
>
Received on Thursday, 7 June 2012 14:06:49 UTC

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