Hi Rupert,
This is a reminder in case you missed this e-mail.
Cristian
2013/9/3 Cristian Petroaca <cristian.petro...@gmail.com>
> 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
>>
>
>
