Ok, then to sum it up we would have :
1. Coref
"stanbol.enhancer.nlp.coref" {
"isRepresentative" : true/false, // whether this token or chunk is the
representative mention in the chain
"mentions" : [ { "type" : "Token", // type of element which refers to
this token/chunk
"start": 123 , // start index of the mentioning element
"end": 130 // end index of the mentioning element
}, ...
],
"class" : ""class" : "org.apache.stanbol.enhancer.nlp.coref.CorefTag"
}
2. Dependency tree
"stanbol.enhancer.nlp.dependency" : {
"relations" : [ { "tag" : "nsubj", //type of relation - Stanford NLP
notation
"dep" : 12, // type of relation - Stanbol NLP mapped
value - ordinal number in enum Dependency
"role" : "gov/dep", // whether this token is the depender or the dependee
"type" : "Token", // type of element with which this token is in relation
"start" : 123, // start index of the relating token
"end" : 130 // end index of the relating token
},
...
]
"class" : "org.apache.stanbol.enhancer.nlp.dependency.DependencyTag"
}
2013/9/2 Rupert Westenthaler <rupert.westentha...@gmail.com>
> Hi Cristian,
>
> let me provide some feedback to your proposals:
>
> ### Referring other Spans
>
> Both suggested annotations require to link other spans (Sentence,
> Chunk or Token). For that we should introduce a JSON element used for
> referring those elements and use it for all usages.
>
> In the java model this would allow you to have a reference to the
> other Span (Sentence, Chunk, Token). In the serialized form you would
> have JSON elements with the "type", "start" and "end" attributes as
> those three uniquely identify any span.
>
> Here an example based on the "mention" attribute as defined by the
> proposed "org.apache.stanbol.enhancer.nlp.coref.CorefTag"
>
> ...
> "mentions" : [ {
> "type" : "Token",
> "start": 123 ,
> "end": 130 } ,{
> "type" : "Token",
> "start": 157 ,
> "end": 165 }],
> ...
>
> Similar token links in
> "org.apache.stanbol.enhancer.nlp.dependency.DependencyTag" should also
> use this model.
>
> ### Usage of Controlled Vocabularies
>
> In addition the DependencyTag also seams to use a controlled
> vocabulary (e.g. 'nsubj', 'conj_and' ...). In such cases the Stanbol
> NLP module tries to define those in some kind of Ontology. For POS
> tags we use OLIA ontology [1]. This is important as most NLP
> frameworks will use different strings and we need to unify those to
> commons IDs so that component that consume those data do not depend on
> a specific NLP tool.
>
> Because the usage of Ontologies within Java is not well supported. The
> Stanbol NLP module defines Java Enumerations for those Ontologies such
> as the POS type enumeration [2].
>
> Both the Java Model as well as the JSON serialization do support both
> (1) the lexical tag as used by the NLP tool and (2) the mapped
> concept. In the Java API via two different methods and in the JSON
> serialization via two separate keys.
>
> To make this more clear here an example for a POS annotation of a proper
> noun.
>
> "stanbol.enhancer.nlp.pos" : {
> "tag" : "PN",
> "pos" : 53,
> "class" : "org.apache.stanbol.enhancer.nlp.pos.PosTag",
> "prob" : 0.95
> }
>
> where
>
> "tag" : "PN"
>
> is the lexical form as used by the NLP tool and
>
> "pos" : 53
>
> refers to the ordinal number of the entry "ProperNoun" in the POS
> enumeration
>
> IMO the "type" property of DependencyTag should use a similar design.
>
> best
> Rupert
>
> [1] http://olia.nlp2rdf.org/
> [2]
> http://svn.apache.org/repos/asf/stanbol/trunk/enhancer/generic/nlp/src/main/java/org/apache/stanbol/enhancer/nlp/pos/Pos.java
>
> On Sun, Sep 1, 2013 at 8:09 PM, Cristian Petroaca
> <cristian.petro...@gmail.com> wrote:
> > Sorry, pressed sent too soon :).
> >
> > Continued :
> >
> > nsubj(met-4, Mary-1), conj_and(Mary-1, Tom-3), nsubj(met-4, Tom-3),
> > root(ROOT-0, met-4), nn(today-6, Danny-5), tmod(met-4, today-6)]
> >
> > Given this, we can have for each "Token" an additional dependency
> > annotation :
> >
> > "stanbol.enhancer.nlp.dependency" : {
> > "tag" : //is it necessary?
> > "relations" : [ { "type" : "nsubj", //type of relation
> > "role" : "gov/dep", //whether it is depender or the dependee
> > "dependencyValue" : "met", // the word with which the token has a
> relation
> > "dependencyIndexInSentence" : "2" //the index of the dependency in the
> > current sentence
> > }
> > ...
> > ]
> > "class" :
> > "org.apache.stanbol.enhancer.nlp.dependency.DependencyTag"
> > }
> >
> > 2013/9/1 Cristian Petroaca <cristian.petro...@gmail.com>
> >
> >> Related to the Stanford Dependency Tree Feature, this is the way the
> >> output from the tool looks like for this sentence : "Mary and Tom met
> Danny
> >> today" :
> >>
> >>
> >> 2013/8/30 Cristian Petroaca <cristian.petro...@gmail.com>
> >>
> >>> Hi Rupert,
> >>>
> >>> Ok, so after looking at the JSON output from the Stanford NLP Server
> and
> >>> the coref module I'm thinking I can represent the coreference
> information
> >>> this way:
> >>> Each "Token" or "Chunk" will contain an additional coref annotation
> with
> >>> the following structure :
> >>>
> >>> "stanbol.enhancer.nlp.coref" {
> >>> "tag" : //does this need to exist?
> >>> "isRepresentative" : true/false, // whether this token or chunk is
> >>> the representative mention in the chain
> >>> "mentions" : [ { "sentenceNo" : 1 //the sentence in which the
> mention
> >>> is found
> >>> "startWord" : 2 //the first word making up
> the
> >>> mention
> >>> "endWord" : 3 //the last word making up the
> >>> mention
> >>> }, ...
> >>> ],
> >>> "class" : ""class" :
> "org.apache.stanbol.enhancer.nlp.coref.CorefTag"
> >>> }
> >>>
> >>> The CorefTag should resemble this model.
> >>>
> >>> What do you think?
> >>>
> >>> Cristian
> >>>
> >>>
> >>> 2013/8/24 Rupert Westenthaler <rupert.westentha...@gmail.com>
> >>>
> >>>> Hi Cristian,
> >>>>
> >>>> you can not directly call StanfordNLP components from Stanbol, but you
> >>>> have to extend the RESTful service to include the information you
> >>>> need. The main reason for that is that the license of StanfordNLP is
> >>>> not compatible with the Apache Software License. So Stanbol can not
> >>>> directly link to the StanfordNLP API.
> >>>>
> >>>> You will need to
> >>>>
> >>>> 1. define an additional class {yourTag} extends Tag<{yourType}> class
> >>>> in the o.a.s.enhancer.nlp module
> >>>> 2. add JSON parsing and serialization support for this tag to the
> >>>> o.a.s.enhancer.nlp.json module (see e.g. PosTagSupport as an example)
> >>>>
> >>>> As (1) would be necessary anyway the only additional thing you need to
> >>>> develop is (2). After that you can add {yourTag} instance to the
> >>>> AnalyzedText in the StanfornNLP integration. The
> >>>> RestfulNlpAnalysisEngine will parse them from the response. All
> >>>> engines executed after the RestfulNlpAnalysisEngine will have access
> >>>> to your annotations.
> >>>>
> >>>> If you have a design for {yourTag} - the model you would like to use
> >>>> to represent your data - I can help with (1) and (2).
> >>>>
> >>>> best
> >>>> Rupert
> >>>>
> >>>>
> >>>> On Fri, Aug 23, 2013 at 5:11 PM, Cristian Petroaca
> >>>> <cristian.petro...@gmail.com> wrote:
> >>>> > Hi Rupert,
> >>>> >
> >>>> > Thanks for the info. Looking at the standbol-stanfordnlp project I
> see
> >>>> that
> >>>> > the stanford nlp is not implemented as an EnhancementEngine but
> rather
> >>>> it
> >>>> > is used directly in a Jetty Server instance. How does that fit into
> the
> >>>> > Stanbol stack? For example how can I call the StanfordNlpAnalyzer's
> >>>> routine
> >>>> > from my TripleExtractionEnhancementEngine which lives in the Stanbol
> >>>> stack?
> >>>> >
> >>>> > Thanks,
> >>>> > Cristian
> >>>> >
> >>>> >
> >>>> > 2013/8/12 Rupert Westenthaler <rupert.westentha...@gmail.com>
> >>>> >
> >>>> >> Hi Cristian,
> >>>> >>
> >>>> >> Sorry for the late response, but I was offline for the last two
> weeks
> >>>> >>
> >>>> >> On Fri, Aug 2, 2013 at 9:19 PM, Cristian Petroaca
> >>>> >> <cristian.petro...@gmail.com> wrote:
> >>>> >> > Hi Rupert,
> >>>> >> >
> >>>> >> > After doing some tests it seems that the Stanford NLP coreference
> >>>> module
> >>>> >> is
> >>>> >> > much more accurate than the Open NLP one.So I decided to extend
> >>>> Stanford
> >>>> >> > NLP to add coreference there.
> >>>> >>
> >>>> >> The Stanford NLP integration is not part of the Stanbol codebase
> >>>> >> because the licenses are not compatible.
> >>>> >>
> >>>> >> You can find the Stanford NLP integration on
> >>>> >>
> >>>> >> https://github.com/westei/stanbol-stanfordnlp
> >>>> >>
> >>>> >> just create a fork and send pull requests.
> >>>> >>
> >>>> >>
> >>>> >> > Could you add the necessary projects on the branch? And also
> remove
> >>>> the
> >>>> >> > Open NLP ones?
> >>>> >> >
> >>>> >>
> >>>> >> Currently the branch
> >>>> >>
> >>>> >>
> >>>> >>
> >>>>
> http://svn.apache.org/repos/asf/stanbol/branches/nlp-dep-tree-and-co-ref/
> >>>> >>
> >>>> >> only contains the "nlp" and the "nlp-json" modules. IMO those
> should
> >>>> >> be enough for adding coreference support.
> >>>> >>
> >>>> >> IMO you will need to
> >>>> >>
> >>>> >> * add an model for representing coreference to the nlp module
> >>>> >> * add parsing and serializing support to the nlp-json module
> >>>> >> * add the implementation to your fork of the stanbol-stanfordnlp
> >>>> project
> >>>> >>
> >>>> >> best
> >>>> >> Rupert
> >>>> >>
> >>>> >>
> >>>> >>
> >>>> >> > Thanks,
> >>>> >> > Cristian
> >>>> >> >
> >>>> >> >
> >>>> >> > 2013/7/5 Rupert Westenthaler <rupert.westentha...@gmail.com>
> >>>> >> >
> >>>> >> >> Hi Cristian,
> >>>> >> >>
> >>>> >> >> I created the branch at
> >>>> >> >>
> >>>> >> >>
> >>>> >> >>
> >>>> >>
> >>>>
> http://svn.apache.org/repos/asf/stanbol/branches/nlp-dep-tree-and-co-ref/
> >>>> >> >>
> >>>> >> >> ATM in contains only the "nlp" and "nlp-json" module. Let me
> know
> >>>> if
> >>>> >> >> you would like to have more
> >>>> >> >>
> >>>> >> >> best
> >>>> >> >> Rupert
> >>>> >> >>
> >>>> >> >>
> >>>> >> >>
> >>>> >> >> On Thu, Jul 4, 2013 at 10:14 AM, Cristian Petroaca
> >>>> >> >> <cristian.petro...@gmail.com> wrote:
> >>>> >> >> > Hi Rupert,
> >>>> >> >> >
> >>>> >> >> > I created jiras :
> >>>> https://issues.apache.org/jira/browse/STANBOL-1132and
> >>>> >> >> > https://issues.apache.org/jira/browse/STANBOL-1133. The
> >>>> original one
> >>>> >> in
> >>>> >> >> > dependent upon these.
> >>>> >> >> > Please let me know when I can start using the branch.
> >>>> >> >> >
> >>>> >> >> > Thanks,
> >>>> >> >> > Cristian
> >>>> >> >> >
> >>>> >> >> >
> >>>> >> >> > 2013/6/27 Cristian Petroaca <cristian.petro...@gmail.com>
> >>>> >> >> >
> >>>> >> >> >>
> >>>> >> >> >>
> >>>> >> >> >>
> >>>> >> >> >> 2013/6/27 Rupert Westenthaler <rupert.westentha...@gmail.com
> >
> >>>> >> >> >>
> >>>> >> >> >>> On Thu, Jun 27, 2013 at 3:12 PM, Cristian Petroaca
> >>>> >> >> >>> <cristian.petro...@gmail.com> wrote:
> >>>> >> >> >>> > Sorry, I meant the Stanbol NLP API, not Stanford in my
> >>>> previous
> >>>> >> >> e-mail.
> >>>> >> >> >>> By
> >>>> >> >> >>> > the way, does Open NLP have the ability to build
> dependency
> >>>> trees?
> >>>> >> >> >>> >
> >>>> >> >> >>>
> >>>> >> >> >>> AFAIK OpenNLP does not provide this feature.
> >>>> >> >> >>>
> >>>> >> >> >>
> >>>> >> >> >> Then , since the Stanford NLP lib is also integrated into
> >>>> Stanbol,
> >>>> >> I'll
> >>>> >> >> >> take a look at how I can extend its integration to include
> the
> >>>> >> >> dependency
> >>>> >> >> >> tree feature.
> >>>> >> >> >>
> >>>> >> >> >>>
> >>>> >> >> >>>
> >>>> >> >> >> >
> >>>> >> >> >>> > 2013/6/23 Cristian Petroaca <cristian.petro...@gmail.com>
> >>>> >> >> >>> >
> >>>> >> >> >>> >> Hi Rupert,
> >>>> >> >> >>> >>
> >>>> >> >> >>> >> I created jira
> >>>> >> https://issues.apache.org/jira/browse/STANBOL-1121.
> >>>> >> >> >>> >> As you suggested I would start with extending the
> Stanford
> >>>> NLP
> >>>> >> with
> >>>> >> >> >>> >> co-reference resolution but I think also with dependency
> >>>> trees
> >>>> >> >> because
> >>>> >> >> >>> I
> >>>> >> >> >>> >> also need to know the Subject of the sentence and the
> object
> >>>> >> that it
> >>>> >> >> >>> >> affects, right?
> >>>> >> >> >>> >>
> >>>> >> >> >>> >> Given that I need to extend the Stanford NLP API in
> Stanbol
> >>>> for
> >>>> >> >> >>> >> co-reference and dependency trees, how do I proceed with
> >>>> this?
> >>>> >> Do I
> >>>> >> >> >>> create
> >>>> >> >> >>> >> 2 new sub-tasks to the already opened Jira? After that
> can I
> >>>> >> start
> >>>> >> >> >>> >> implementing on my local copy of Stanbol and when I'm
> done
> >>>> I'll
> >>>> >> send
> >>>> >> >> >>> you
> >>>> >> >> >>> >> guys the patch fo review?
> >>>> >> >> >>> >>
> >>>> >> >> >>>
> >>>> >> >> >>> I would create two "New Feature" type Issues one for adding
> >>>> support
> >>>> >> >> >>> for "dependency trees" and the other for "co-reference"
> >>>> support. You
> >>>> >> >> >>> should also define "depends on" relations between
> STANBOL-1121
> >>>> and
> >>>> >> >> >>> those two new issues.
> >>>> >> >> >>>
> >>>> >> >> >>> Sub-task could also work, but as adding those features would
> >>>> be also
> >>>> >> >> >>> interesting for other things I would rather define them as
> >>>> separate
> >>>> >> >> >>> issues.
> >>>> >> >> >>>
> >>>> >> >> >>>
> >>>> >> >> >> 2 New Features connected with the original jira it is then.
> >>>> >> >> >>
> >>>> >> >> >>
> >>>> >> >> >>> If you would prefer to work in an own branch please tell me.
> >>>> This
> >>>> >> >> >>> could have the advantage that patches would not be affected
> by
> >>>> >> changes
> >>>> >> >> >>> in the trunk.
> >>>> >> >> >>>
> >>>> >> >> >>> Yes, a separate branch sounds good.
> >>>> >> >> >>
> >>>> >> >> >> best
> >>>> >> >> >>> Rupert
> >>>> >> >> >>>
> >>>> >> >> >>> >> Regards,
> >>>> >> >> >>> >> Cristian
> >>>> >> >> >>> >>
> >>>> >> >> >>> >>
> >>>> >> >> >>> >> 2013/6/18 Rupert Westenthaler <
> >>>> rupert.westentha...@gmail.com>
> >>>> >> >> >>> >>
> >>>> >> >> >>> >>> On Mon, Jun 17, 2013 at 10:18 PM, Cristian Petroaca
> >>>> >> >> >>> >>> <cristian.petro...@gmail.com> wrote:
> >>>> >> >> >>> >>> > Hi Rupert,
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> > Agreed on the
> >>>> >> >> >>> SettingAnnotation/ParticipantAnnotation/OccurentAnnotation
> >>>> >> >> >>> >>> > data structure.
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> > Should I open up a Jira for all of this in order to
> >>>> >> encapsulate
> >>>> >> >> this
> >>>> >> >> >>> >>> > information and establish the goals and these initial
> >>>> steps
> >>>> >> >> towards
> >>>> >> >> >>> >>> these
> >>>> >> >> >>> >>> > goals?
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> Yes please. A JIRA issue for this work would be great.
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> > How should I proceed further? Should I create some
> design
> >>>> >> >> documents
> >>>> >> >> >>> that
> >>>> >> >> >>> >>> > need to be reviewed?
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> Usually it is the best to write design related text
> >>>> directly in
> >>>> >> >> JIRA
> >>>> >> >> >>> >>> by using Markdown [1] syntax. This will allow us later
> to
> >>>> use
> >>>> >> this
> >>>> >> >> >>> >>> text directly for the documentation on the Stanbol
> Webpage.
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> best
> >>>> >> >> >>> >>> Rupert
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> [1] http://daringfireball.net/projects/markdown/
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> > Regards,
> >>>> >> >> >>> >>> > Cristian
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> > 2013/6/17 Rupert Westenthaler <
> >>>> rupert.westentha...@gmail.com>
> >>>> >> >> >>> >>> >
> >>>> >> >> >>> >>> >> On Thu, Jun 13, 2013 at 8:22 PM, Cristian Petroaca
> >>>> >> >> >>> >>> >> <cristian.petro...@gmail.com> wrote:
> >>>> >> >> >>> >>> >> > HI Rupert,
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > First of all thanks for the detailed suggestions.
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > 2013/6/12 Rupert Westenthaler <
> >>>> >> rupert.westentha...@gmail.com>
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> >> Hi Cristian, all
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> really interesting use case!
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> In this mail I will try to give some suggestions
> on
> >>>> how
> >>>> >> this
> >>>> >> >> >>> could
> >>>> >> >> >>> >>> >> >> work out. This suggestions are mainly based on
> >>>> experiences
> >>>> >> >> and
> >>>> >> >> >>> >>> lessons
> >>>> >> >> >>> >>> >> >> learned in the LIVE [2] project where we built an
> >>>> >> information
> >>>> >> >> >>> system
> >>>> >> >> >>> >>> >> >> for the Olympic Games in Peking. While this
> Project
> >>>> >> excluded
> >>>> >> >> the
> >>>> >> >> >>> >>> >> >> extraction of Events from unstructured text
> (because
> >>>> the
> >>>> >> >> Olympic
> >>>> >> >> >>> >>> >> >> Information System was already providing event
> data
> >>>> as XML
> >>>> >> >> >>> messages)
> >>>> >> >> >>> >>> >> >> the semantic search capabilities of this system
> >>>> where very
> >>>> >> >> >>> similar
> >>>> >> >> >>> >>> as
> >>>> >> >> >>> >>> >> >> the one described by your use case.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> IMHO you are not only trying to extract relations,
> >>>> but a
> >>>> >> >> formal
> >>>> >> >> >>> >>> >> >> representation of the situation described by the
> >>>> text. So
> >>>> >> >> lets
> >>>> >> >> >>> >>> assume
> >>>> >> >> >>> >>> >> >> that the goal is to Annotate a Setting (or
> Situation)
> >>>> >> >> described
> >>>> >> >> >>> in
> >>>> >> >> >>> >>> the
> >>>> >> >> >>> >>> >> >> text - a fise:SettingAnnotation.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> The DOLCE foundational ontology [1] gives some
> >>>> advices on
> >>>> >> >> how to
> >>>> >> >> >>> >>> model
> >>>> >> >> >>> >>> >> >> those. The important relation for modeling this
> >>>> >> >> Participation:
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> PC(x, y, t) → (ED(x) ∧ PD(y) ∧ T(t))
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> where ..
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> * ED are Endurants (continuants): Endurants do
> have
> >>>> an
> >>>> >> >> >>> identity so
> >>>> >> >> >>> >>> we
> >>>> >> >> >>> >>> >> >> would typically refer to them as Entities
> referenced
> >>>> by a
> >>>> >> >> >>> setting.
> >>>> >> >> >>> >>> >> >> Note that this includes physical, non-physical as
> >>>> well as
> >>>> >> >> >>> >>> >> >> social-objects.
> >>>> >> >> >>> >>> >> >> * PD are Perdurants (occurrents): Perdurants are
> >>>> >> entities
> >>>> >> >> that
> >>>> >> >> >>> >>> >> >> happen in time. This refers to Events, Activities
> ...
> >>>> >> >> >>> >>> >> >> * PC are Participation: It is an time indexed
> >>>> relation
> >>>> >> where
> >>>> >> >> >>> >>> >> >> Endurants participate in Perdurants
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> Modeling this in RDF requires to define some
> >>>> intermediate
> >>>> >> >> >>> resources
> >>>> >> >> >>> >>> >> >> because RDF does not allow for n-ary relations.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> * fise:SettingAnnotation: It is really handy to
> >>>> define
> >>>> >> one
> >>>> >> >> >>> resource
> >>>> >> >> >>> >>> >> >> being the context for all described data. I would
> >>>> call
> >>>> >> this
> >>>> >> >> >>> >>> >> >> "fise:SettingAnnotation" and define it as a
> >>>> sub-concept to
> >>>> >> >> >>> >>> >> >> fise:Enhancement. All further enhancement about
> the
> >>>> >> extracted
> >>>> >> >> >>> >>> Setting
> >>>> >> >> >>> >>> >> >> would define a "fise:in-setting" relation to it.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> * fise:ParticipantAnnotation: Is used to annotate
> >>>> that
> >>>> >> >> >>> Endurant is
> >>>> >> >> >>> >>> >> >> participating on a setting (fise:in-setting
> >>>> >> >> >>> fise:SettingAnnotation).
> >>>> >> >> >>> >>> >> >> The Endurant itself is described by existing
> >>>> >> >> fise:TextAnnotaion
> >>>> >> >> >>> (the
> >>>> >> >> >>> >>> >> >> mentions) and fise:EntityAnnotation (suggested
> >>>> Entities).
> >>>> >> >> >>> Basically
> >>>> >> >> >>> >>> >> >> the fise:ParticipantAnnotation will allow an
> >>>> >> >> EnhancementEngine
> >>>> >> >> >>> to
> >>>> >> >> >>> >>> >> >> state that several mentions (in possible different
> >>>> >> >> sentences) do
> >>>> >> >> >>> >>> >> >> represent the same Endurant as participating in
> the
> >>>> >> Setting.
> >>>> >> >> In
> >>>> >> >> >>> >>> >> >> addition it would be possible to use the dc:type
> >>>> property
> >>>> >> >> >>> (similar
> >>>> >> >> >>> >>> as
> >>>> >> >> >>> >>> >> >> for fise:TextAnnotation) to refer to the role(s)
> of
> >>>> an
> >>>> >> >> >>> participant
> >>>> >> >> >>> >>> >> >> (e.g. the set: Agent (intensionally performs an
> >>>> action)
> >>>> >> Cause
> >>>> >> >> >>> >>> >> >> (unintentionally e.g. a mud slide), Patient (a
> >>>> passive
> >>>> >> role
> >>>> >> >> in
> >>>> >> >> >>> an
> >>>> >> >> >>> >>> >> >> activity) and Instrument (aids an process)), but
> I am
> >>>> >> >> wondering
> >>>> >> >> >>> if
> >>>> >> >> >>> >>> one
> >>>> >> >> >>> >>> >> >> could extract those information.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> * fise:OccurrentAnnotation: is used to annotate a
> >>>> >> Perdurant
> >>>> >> >> in
> >>>> >> >> >>> the
> >>>> >> >> >>> >>> >> >> context of the Setting. Also
> >>>> fise:OccurrentAnnotation can
> >>>> >> >> link
> >>>> >> >> >>> to
> >>>> >> >> >>> >>> >> >> fise:TextAnnotaion (typically verbs in the text
> >>>> defining
> >>>> >> the
> >>>> >> >> >>> >>> >> >> perdurant) as well as fise:EntityAnnotation
> >>>> suggesting
> >>>> >> well
> >>>> >> >> >>> known
> >>>> >> >> >>> >>> >> >> Events in a knowledge base (e.g. a Election in a
> >>>> country,
> >>>> >> or
> >>>> >> >> an
> >>>> >> >> >>> >>> >> >> upraising ...). In addition
> fise:OccurrentAnnotation
> >>>> can
> >>>> >> >> define
> >>>> >> >> >>> >>> >> >> dc:has-participant links to
> >>>> fise:ParticipantAnnotation. In
> >>>> >> >> this
> >>>> >> >> >>> case
> >>>> >> >> >>> >>> >> >> it is explicitly stated hat an Endurant (the
> >>>> >> >> >>> >>> >> >> fise:ParticipantAnnotation) involved in this
> >>>> Perturant
> >>>> >> (the
> >>>> >> >> >>> >>> >> >> fise:OccurrentAnnotation). As Occurrences are
> >>>> temporal
> >>>> >> >> indexed
> >>>> >> >> >>> this
> >>>> >> >> >>> >>> >> >> annotation should also support properties for
> >>>> defining the
> >>>> >> >> >>> >>> >> >> xsd:dateTime for the start/end.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> Indeed, an event based data structure makes a lot
> of
> >>>> sense
> >>>> >> >> with
> >>>> >> >> >>> the
> >>>> >> >> >>> >>> >> remark
> >>>> >> >> >>> >>> >> > that you probably won't be able to always extract
> the
> >>>> date
> >>>> >> >> for a
> >>>> >> >> >>> >>> given
> >>>> >> >> >>> >>> >> > setting(situation).
> >>>> >> >> >>> >>> >> > There are 2 thing which are unclear though.
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > 1. Perdurant : You could have situations in which
> the
> >>>> >> object
> >>>> >> >> upon
> >>>> >> >> >>> >>> which
> >>>> >> >> >>> >>> >> the
> >>>> >> >> >>> >>> >> > Subject ( or Endurant ) is acting is not a
> transitory
> >>>> >> object (
> >>>> >> >> >>> such
> >>>> >> >> >>> >>> as an
> >>>> >> >> >>> >>> >> > event, activity ) but rather another Endurant. For
> >>>> example
> >>>> >> we
> >>>> >> >> can
> >>>> >> >> >>> >>> have
> >>>> >> >> >>> >>> >> the
> >>>> >> >> >>> >>> >> > phrase "USA invades Irak" where "USA" is the
> Endurant
> >>>> (
> >>>> >> >> Subject )
> >>>> >> >> >>> >>> which
> >>>> >> >> >>> >>> >> > performs the action of "invading" on another
> >>>> Eundurant,
> >>>> >> namely
> >>>> >> >> >>> >>> "Irak".
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> By using CAOS, USA would be the Agent and Iraq the
> >>>> Patient.
> >>>> >> Both
> >>>> >> >> >>> are
> >>>> >> >> >>> >>> >> Endurants. The activity "invading" would be the
> >>>> Perdurant. So
> >>>> >> >> >>> ideally
> >>>> >> >> >>> >>> >> you would have a "fise:SettingAnnotation" with:
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * fise:ParticipantAnnotation for USA with the
> dc:type
> >>>> >> >> caos:Agent,
> >>>> >> >> >>> >>> >> linking to a fise:TextAnnotation for "USA" and a
> >>>> >> >> >>> fise:EntityAnnotation
> >>>> >> >> >>> >>> >> linking to dbpedia:United_States
> >>>> >> >> >>> >>> >> * fise:ParticipantAnnotation for Iraq with the
> dc:type
> >>>> >> >> >>> caos:Patient,
> >>>> >> >> >>> >>> >> linking to a fise:TextAnnotation for "Irak" and a
> >>>> >> >> >>> >>> >> fise:EntityAnnotation linking to dbpedia:Iraq
> >>>> >> >> >>> >>> >> * fise:OccurrentAnnotation for "invades" with the
> >>>> dc:type
> >>>> >> >> >>> >>> >> caos:Activity, linking to a fise:TextAnnotation for
> >>>> "invades"
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> > 2. Where does the verb, which links the Subject and
> >>>> the
> >>>> >> Object
> >>>> >> >> >>> come
> >>>> >> >> >>> >>> into
> >>>> >> >> >>> >>> >> > this? I imagined that the Endurant would have a
> >>>> >> dc:"property"
> >>>> >> >> >>> where
> >>>> >> >> >>> >>> the
> >>>> >> >> >>> >>> >> > property = verb which links to the Object in noun
> >>>> form. For
> >>>> >> >> >>> example
> >>>> >> >> >>> >>> take
> >>>> >> >> >>> >>> >> > again the sentence "USA invades Irak". You would
> have
> >>>> the
> >>>> >> >> "USA"
> >>>> >> >> >>> >>> Entity
> >>>> >> >> >>> >>> >> with
> >>>> >> >> >>> >>> >> > dc:invader which points to the Object "Irak". The
> >>>> Endurant
> >>>> >> >> would
> >>>> >> >> >>> >>> have as
> >>>> >> >> >>> >>> >> > many dc:"property" elements as there are verbs
> which
> >>>> link
> >>>> >> it
> >>>> >> >> to
> >>>> >> >> >>> an
> >>>> >> >> >>> >>> >> Object.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> As explained above you would have a
> >>>> fise:OccurrentAnnotation
> >>>> >> >> that
> >>>> >> >> >>> >>> >> represents the Perdurant. The information that the
> >>>> activity
> >>>> >> >> >>> mention in
> >>>> >> >> >>> >>> >> the text is "invades" would be by linking to a
> >>>> >> >> >>> fise:TextAnnotation. If
> >>>> >> >> >>> >>> >> you can also provide an Ontology for Tasks that
> defines
> >>>> >> >> >>> >>> >> "myTasks:invade" the fise:OccurrentAnnotation could
> >>>> also link
> >>>> >> >> to an
> >>>> >> >> >>> >>> >> fise:EntityAnnotation for this concept.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> best
> >>>> >> >> >>> >>> >> Rupert
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > ### Consuming the data:
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> I think this model should be sufficient for
> >>>> use-cases as
> >>>> >> >> >>> described
> >>>> >> >> >>> >>> by
> >>>> >> >> >>> >>> >> you.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> Users would be able to consume data on the setting
> >>>> level.
> >>>> >> >> This
> >>>> >> >> >>> can
> >>>> >> >> >>> >>> be
> >>>> >> >> >>> >>> >> >> done my simple retrieving all
> >>>> fise:ParticipantAnnotation
> >>>> >> as
> >>>> >> >> >>> well as
> >>>> >> >> >>> >>> >> >> fise:OccurrentAnnotation linked with a setting.
> BTW
> >>>> this
> >>>> >> was
> >>>> >> >> the
> >>>> >> >> >>> >>> >> >> approach used in LIVE [2] for semantic search. It
> >>>> allows
> >>>> >> >> >>> queries for
> >>>> >> >> >>> >>> >> >> Settings that involve specific Entities e.g. you
> >>>> could
> >>>> >> filter
> >>>> >> >> >>> for
> >>>> >> >> >>> >>> >> >> Settings that involve a {Person},
> >>>> activities:Arrested and
> >>>> >> a
> >>>> >> >> >>> specific
> >>>> >> >> >>> >>> >> >> {Upraising}. However note that with this approach
> >>>> you will
> >>>> >> >> get
> >>>> >> >> >>> >>> results
> >>>> >> >> >>> >>> >> >> for Setting where the {Person} participated and an
> >>>> other
> >>>> >> >> person
> >>>> >> >> >>> was
> >>>> >> >> >>> >>> >> >> arrested.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> An other possibility would be to process
> enhancement
> >>>> >> results
> >>>> >> >> on
> >>>> >> >> >>> the
> >>>> >> >> >>> >>> >> >> fise:OccurrentAnnotation. This would allow to a
> much
> >>>> >> higher
> >>>> >> >> >>> >>> >> >> granularity level (e.g. it would allow to
> correctly
> >>>> answer
> >>>> >> >> the
> >>>> >> >> >>> query
> >>>> >> >> >>> >>> >> >> used as an example above). But I am wondering if
> the
> >>>> >> quality
> >>>> >> >> of
> >>>> >> >> >>> the
> >>>> >> >> >>> >>> >> >> Setting extraction will be sufficient for this. I
> >>>> have
> >>>> >> also
> >>>> >> >> >>> doubts
> >>>> >> >> >>> >>> if
> >>>> >> >> >>> >>> >> >> this can be still realized by using semantic
> >>>> indexing to
> >>>> >> >> Apache
> >>>> >> >> >>> Solr
> >>>> >> >> >>> >>> >> >> or if it would be better/necessary to store
> results
> >>>> in a
> >>>> >> >> >>> TripleStore
> >>>> >> >> >>> >>> >> >> and using SPARQL for retrieval.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> The methodology and query language used by YAGO
> [3]
> >>>> is
> >>>> >> also
> >>>> >> >> very
> >>>> >> >> >>> >>> >> >> relevant for this (especially note chapter 7
> SPOTL(X)
> >>>> >> >> >>> >>> Representation).
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> An other related Topic is the enrichment of
> Entities
> >>>> >> >> (especially
> >>>> >> >> >>> >>> >> >> Events) in knowledge bases based on Settings
> >>>> extracted
> >>>> >> form
> >>>> >> >> >>> >>> Documents.
> >>>> >> >> >>> >>> >> >> As per definition - in DOLCE - Perdurants are
> >>>> temporal
> >>>> >> >> indexed.
> >>>> >> >> >>> That
> >>>> >> >> >>> >>> >> >> means that at the time when added to a knowledge
> >>>> base they
> >>>> >> >> might
> >>>> >> >> >>> >>> still
> >>>> >> >> >>> >>> >> >> be in process. So the creation, enriching and
> >>>> refinement
> >>>> >> of
> >>>> >> >> such
> >>>> >> >> >>> >>> >> >> Entities in a the knowledge base seams to be
> >>>> critical for
> >>>> >> a
> >>>> >> >> >>> System
> >>>> >> >> >>> >>> >> >> like described in your use-case.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> On Tue, Jun 11, 2013 at 9:09 PM, Cristian Petroaca
> >>>> >> >> >>> >>> >> >> <cristian.petro...@gmail.com> wrote:
> >>>> >> >> >>> >>> >> >> >
> >>>> >> >> >>> >>> >> >> > First of all I have to mention that I am new in
> the
> >>>> >> field
> >>>> >> >> of
> >>>> >> >> >>> >>> semantic
> >>>> >> >> >>> >>> >> >> > technologies, I've started to read about them in
> >>>> the
> >>>> >> last
> >>>> >> >> 4-5
> >>>> >> >> >>> >>> >> >> months.Having
> >>>> >> >> >>> >>> >> >> > said that I have a high level overview of what
> is
> >>>> a good
> >>>> >> >> >>> approach
> >>>> >> >> >>> >>> to
> >>>> >> >> >>> >>> >> >> solve
> >>>> >> >> >>> >>> >> >> > this problem. There are a number of papers on
> the
> >>>> >> internet
> >>>> >> >> >>> which
> >>>> >> >> >>> >>> >> describe
> >>>> >> >> >>> >>> >> >> > what steps need to be taken such as : named
> entity
> >>>> >> >> >>> recognition,
> >>>> >> >> >>> >>> >> >> > co-reference resolution, pos tagging and others.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> The Stanbol NLP processing module currently only
> >>>> supports
> >>>> >> >> >>> sentence
> >>>> >> >> >>> >>> >> >> detection, tokenization, POS tagging, Chunking,
> NER
> >>>> and
> >>>> >> >> lemma.
> >>>> >> >> >>> >>> support
> >>>> >> >> >>> >>> >> >> for co-reference resolution and dependency trees
> is
> >>>> >> currently
> >>>> >> >> >>> >>> missing.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> Stanford NLP is already integrated with Stanbol
> [4].
> >>>> At
> >>>> >> the
> >>>> >> >> >>> moment
> >>>> >> >> >>> >>> it
> >>>> >> >> >>> >>> >> >> only supports English, but I do already work to
> >>>> include
> >>>> >> the
> >>>> >> >> >>> other
> >>>> >> >> >>> >>> >> >> supported languages. Other NLP framework that is
> >>>> already
> >>>> >> >> >>> integrated
> >>>> >> >> >>> >>> >> >> with Stanbol are Freeling [5] and Talismane [6].
> But
> >>>> note
> >>>> >> >> that
> >>>> >> >> >>> for
> >>>> >> >> >>> >>> all
> >>>> >> >> >>> >>> >> >> those the integration excludes support for
> >>>> co-reference
> >>>> >> and
> >>>> >> >> >>> >>> dependency
> >>>> >> >> >>> >>> >> >> trees.
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> Anyways I am confident that one can implement a
> first
> >>>> >> >> prototype
> >>>> >> >> >>> by
> >>>> >> >> >>> >>> >> >> only using Sentences and POS tags and - if
> available
> >>>> -
> >>>> >> Chunks
> >>>> >> >> >>> (e.g.
> >>>> >> >> >>> >>> >> >> Noun phrases).
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> > I assume that in the Stanbol context, a feature
> like
> >>>> >> Relation
> >>>> >> >> >>> >>> extraction
> >>>> >> >> >>> >>> >> > would be implemented as an EnhancementEngine?
> >>>> >> >> >>> >>> >> > What kind of effort would be required for a
> >>>> co-reference
> >>>> >> >> >>> resolution
> >>>> >> >> >>> >>> tool
> >>>> >> >> >>> >>> >> > integration into Stanbol?
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> Yes in the end it would be an EnhancementEngine. But
> >>>> before
> >>>> >> we
> >>>> >> >> can
> >>>> >> >> >>> >>> >> build such an engine we would need to
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * extend the Stanbol NLP processing API with
> >>>> Annotations for
> >>>> >> >> >>> >>> co-reference
> >>>> >> >> >>> >>> >> * add support for JSON Serialisation/Parsing for
> those
> >>>> >> >> annotation
> >>>> >> >> >>> so
> >>>> >> >> >>> >>> >> that the RESTful NLP Analysis Service can provide
> >>>> >> co-reference
> >>>> >> >> >>> >>> >> information
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> > At this moment I'll be focusing on 2 aspects:
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > 1. Determine the best data structure to encapsulate
> >>>> the
> >>>> >> >> extracted
> >>>> >> >> >>> >>> >> > information. I'll take a closer look at Dolce.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> Don't make to to complex. Defining a proper
> structure to
> >>>> >> >> represent
> >>>> >> >> >>> >>> >> Events will only pay-off if we can also successfully
> >>>> extract
> >>>> >> >> such
> >>>> >> >> >>> >>> >> information form processed texts.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> I would start with
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * fise:SettingAnnotation
> >>>> >> >> >>> >>> >> * {fise:Enhancement} metadata
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * fise:ParticipantAnnotation
> >>>> >> >> >>> >>> >> * {fise:Enhancement} metadata
> >>>> >> >> >>> >>> >> * fise:inSetting {settingAnnotation}
> >>>> >> >> >>> >>> >> * fise:hasMention {textAnnotation}
> >>>> >> >> >>> >>> >> * fise:suggestion {entityAnnotation} (multiple if
> >>>> there
> >>>> >> are
> >>>> >> >> >>> more
> >>>> >> >> >>> >>> >> suggestions)
> >>>> >> >> >>> >>> >> * dc:type one of fise:Agent, fise:Patient,
> >>>> >> fise:Instrument,
> >>>> >> >> >>> >>> fise:Cause
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * fise:OccurrentAnnotation
> >>>> >> >> >>> >>> >> * {fise:Enhancement} metadata
> >>>> >> >> >>> >>> >> * fise:inSetting {settingAnnotation}
> >>>> >> >> >>> >>> >> * fise:hasMention {textAnnotation}
> >>>> >> >> >>> >>> >> * dc:type set to fise:Activity
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> If it turns out that we can extract more, we can add
> >>>> more
> >>>> >> >> >>> structure to
> >>>> >> >> >>> >>> >> those annotations. We might also think about using an
> >>>> own
> >>>> >> >> namespace
> >>>> >> >> >>> >>> >> for those extensions to the annotation structure.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> > 2. Determine how should all of this be integrated
> into
> >>>> >> >> Stanbol.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> Just create an EventExtractionEngine and configure a
> >>>> >> enhancement
> >>>> >> >> >>> chain
> >>>> >> >> >>> >>> >> that does NLP processing and EntityLinking.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> You should have a look at
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * SentimentSummarizationEngine [1] as it does a lot
> of
> >>>> things
> >>>> >> >> with
> >>>> >> >> >>> NLP
> >>>> >> >> >>> >>> >> processing results (e.g. connecting adjectives (via
> >>>> verbs) to
> >>>> >> >> >>> >>> >> nouns/pronouns. So as long we can not use explicit
> >>>> dependency
> >>>> >> >> trees
> >>>> >> >> >>> >>> >> you code will need to do similar things with Nouns,
> >>>> Pronouns
> >>>> >> and
> >>>> >> >> >>> >>> >> Verbs.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> * Disambigutation-MLT engine, as it creates a Java
> >>>> >> >> representation
> >>>> >> >> >>> of
> >>>> >> >> >>> >>> >> present fise:TextAnnotation and fise:EntityAnnotation
> >>>> [2].
> >>>> >> >> >>> Something
> >>>> >> >> >>> >>> >> similar will also be required by the
> >>>> EventExtractionEngine
> >>>> >> for
> >>>> >> >> fast
> >>>> >> >> >>> >>> >> access to such annotations while iterating over the
> >>>> >> Sentences of
> >>>> >> >> >>> the
> >>>> >> >> >>> >>> >> text.
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> best
> >>>> >> >> >>> >>> >> Rupert
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> [1]
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>>
> >>>> >> >> >>>
> >>>> >> >>
> >>>> >>
> >>>>
> https://svn.apache.org/repos/asf/stanbol/trunk/enhancement-engines/sentiment-summarization/src/main/java/org/apache/stanbol/enhancer/engines/sentiment/summarize/SentimentSummarizationEngine.java
> >>>> >> >> >>> >>> >> [2]
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>>
> >>>> >> >> >>>
> >>>> >> >>
> >>>> >>
> >>>>
> https://svn.apache.org/repos/asf/stanbol/trunk/enhancement-engines/disambiguation-mlt/src/main/java/org/apache/stanbol/enhancer/engine/disambiguation/mlt/DisambiguationData.java
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > Thanks
> >>>> >> >> >>> >>> >> >
> >>>> >> >> >>> >>> >> > Hope this helps to bootstrap this discussion
> >>>> >> >> >>> >>> >> >> best
> >>>> >> >> >>> >>> >> >> Rupert
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >> >> --
> >>>> >> >> >>> >>> >> >> | Rupert Westenthaler
> >>>> >> >> rupert.westentha...@gmail.com
> >>>> >> >> >>> >>> >> >> | Bodenlehenstraße 11
> >>>> >> >> >>> ++43-699-11108907
> >>>> >> >> >>> >>> >> >> | A-5500 Bischofshofen
> >>>> >> >> >>> >>> >> >>
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>> >> --
> >>>> >> >> >>> >>> >> | Rupert Westenthaler
> >>>> >> rupert.westentha...@gmail.com
> >>>> >> >> >>> >>> >> | Bodenlehenstraße 11
> >>>> >> >> >>> ++43-699-11108907
> >>>> >> >> >>> >>> >> | A-5500 Bischofshofen
> >>>> >> >> >>> >>> >>
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>> --
> >>>> >> >> >>> >>> | Rupert Westenthaler
> >>>> rupert.westentha...@gmail.com
> >>>> >> >> >>> >>> | Bodenlehenstraße 11
> >>>> >> >> ++43-699-11108907
> >>>> >> >> >>> >>> | A-5500 Bischofshofen
> >>>> >> >> >>> >>>
> >>>> >> >> >>> >>
> >>>> >> >> >>> >>
> >>>> >> >> >>>
> >>>> >> >> >>>
> >>>> >> >> >>>
> >>>> >> >> >>> --
> >>>> >> >> >>> | Rupert Westenthaler
> >>>> rupert.westentha...@gmail.com
> >>>> >> >> >>> | Bodenlehenstraße 11
> >>>> ++43-699-11108907
> >>>> >> >> >>> | A-5500 Bischofshofen
> >>>> >> >> >>>
> >>>> >> >> >>
> >>>> >> >> >>
> >>>> >> >>
> >>>> >> >>
> >>>> >> >>
> >>>> >> >> --
> >>>> >> >> | Rupert Westenthaler rupert.westentha...@gmail.com
> >>>> >> >> | Bodenlehenstraße 11
> >>>> ++43-699-11108907
> >>>> >> >> | A-5500 Bischofshofen
> >>>> >> >>
> >>>> >>
> >>>> >>
> >>>> >>
> >>>> >> --
> >>>> >> | Rupert Westenthaler rupert.westentha...@gmail.com
> >>>> >> | Bodenlehenstraße 11 ++43-699-11108907
> >>>> >> | A-5500 Bischofshofen
> >>>> >>
> >>>>
> >>>>
> >>>>
> >>>> --
> >>>> | Rupert Westenthaler rupert.westentha...@gmail.com
> >>>> | Bodenlehenstraße 11 ++43-699-11108907
> >>>> | A-5500 Bischofshofen
> >>>>
> >>>
> >>>
> >>
>
>
>
> --
> | Rupert Westenthaler rupert.westentha...@gmail.com
> | Bodenlehenstraße 11 ++43-699-11108907
> | A-5500 Bischofshofen
>
