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 >
