The NLP Interchange Format (NIF) is an RDF/OWL-based format that aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. The core of NIF consists of a vocabulary, which can represent Strings as RDF resources. A special URI Design is used to pinpoint annotations to a part of a document. These URIs can then be used to attach arbitrary annotations to the respective character sequence. Employing these URIs, annotations can be published on the Web as Linked Data and interchanged between different NLP tools and applications.

In order to simplify the combination of tools, improve their interoperability and facilitating the use of Linked Data we developed the NLP Interchange Format (NIF). NIF addresses the interoperability problem on three layers: the structural, conceptual and access layer. NIF is based on a Linked Data enabled URI scheme for identifying elements in (hyper-) texts (structural layer) and a comprehensive ontology for describing common NLP terms and concepts (conceptual layer). NIF-aware applications will produce output (and possibly also consume input) adhering to the NIF ontology as REST services (access layer). Other than more centralized solutions such as UIMA and GATE, NIF enables the creation of heterogeneous, distributed and loosely coupled NLP applications, which use the Web as an integration platform. Another benefit is, that a NIF wrapper has to be only created once for a particular tool, but enables the tool to interoperate with a potentially large number of other
tools without additional adaptations. Ultimately, we envision an ecosystem of NLP tools and services to emerge using NIF for exchanging and integrating rich annotations.

We designed NIF to be very light-weight and to reduce the amount of triples to achieve better scalability. The following triples in N3 Syntax express that the string “W3C” on http://www.w3.org/DesignIssues/LinkedData.html (index 22849 to 22852) is linked to the DBpedia resource of “World_Wide_Web_Consortium”:

@prefix ld: <http://www.w3.org/DesignIssues/LinkedData.html#> .
@prefix str: <http://nlp2rdf.lod2.eu/schema/string/> .
@prefix dbo: <http://dbpedia.org/ontology/> .
@prefix scms: <http://ns.aksw.org/scms/> .
@prefix nerd: <http://nerd.eurecom.fr/ontology#> .
ld:offset_22849_22852_W3C str:anchorOf "W3C" .
ld:offset_22849_22852_W3C scms:means dbpedia:World_Wide_Web_Consortium .
ld:offset_22849_22852_W3C a dbo:Organisation , nerd:Organization .


NIF already incorporates the Ontologies of Linguistic Annotation (OLiA) and the Named Entity Recognition and Disambiguation (NERD) ontology. Please get in contact, if you know of further NLP ontologies, which we can reuse and integrate in NIF.

This release consists of the following items:

• The specification of NIF 1.0. This document will guide the further implementation of NIF-enabled services. An average wrapper requires around 200-500 lines of code. The spec integrates several domain ontologies (OLiA, NERD) and will be extended in the future to cover more domains.
• A community portal with a mailing list: nlp2rdf@lists.informatik.uni-leipzig.de . Read how to get involved.
• A reference implementations of NIF 1.0 in Java
  • Release 1.2
  • Source code
• Wrapper implementations for Stanford CoreNLP, SnowballStemmer, OpenNLP, MontyLingua, DBpedia Spotlight, UIMA, Gate (for ANNIE and also generic output), Mallet (alpha)
  • Demo GUI (with links to implementations):
  • List of implementations
• Tutorials and Tutorial Challenges
  • Tutorial: How to call a NIF web service with your favorite SemWeb library
  • Tutorial Challenge: Semantic Search
  • Tutorial Challenge: Multilingual Part-Of-Speech Tagger
  • Tutorial Challenge: Semantic Yellow Pages
• Slides
• A technical report including some evaluation.

We would like to thank our colleagues from AKSW research group and the LOD2 project for their helpful comments and inspiring discussions during the development of NIF. Especially, we would like to thank Christian Chiarcos for his support while using OLiA, the members of the Working Group on Open Data in Linguistics and the students that participated in the NIF field study: Markus Ackermann, Martin Brümmer, Didier Cherix, Marcus Nitzschke, Robert Schulze.

Hello world,

We are happy to announce that LIMES has been extended with an interface that will make linking easier than ever before. The COLANUT (Complex Linking in a NUTshell) interface implements time-efficient schema matching algorithms that allow LIMES to discover and suggest initial class and properties matchings for linking. The whole is embedded in an easy-to-use GUI that allows you to create link specifications easily and download them as XML files or simply to run them online. Check COLANUT out at http://limes.aksw.org/colanut. A technical description can be found here.

And before I forget, two papers centered around linking with LIMES were accepted at OM2011, the ontology matching workshop at ISWC. Come around and get all details on the exciting development around LIMES and Link Discovery in general.

Link on,
Axel

Yet another project for improving the access to Linked Data! It is our pleasure to announce the first version of the Assisted Linked Data Consumption Engine (ALOE). The aim of ALOE project is to assist users during the consumption from and fusion of Linked Data sources. ALOE achieves this goal by discovering class and property mappings across endpoints even when no schema information is available. Moreover, ALOE provides several functions for transforming the data from the source knowledge base into a format that corresponds to that of the target knowledge base. Therewith, ALOE enables lay and experienced users to consume Linked Data with great ease. More information on ALOE can be found at

http://aksw.org/projects/aloe

Cheers,
Axel

We are happy to announce the beta release of RDFaCE (RDFa Content Editor). RDFaCE is an online text editor based on TinyMCE. It supports authoring of RDFa content.

In addition to two classical views for text authoring (WYSIWYG and HTML Source Code view) , RDFaCE  supports two novel views for semantic content authoring namely WYSIWYM (What You See Is What You Mean) and a Triple view (aka. Fact View).

The WYSIWYM displays semantic annotations on top of classical WYSIWYG view which is widely used for Web content creation. It uses dynamic CSS stylesheets to distinguish semantic content from normal content.

The triple view is another semantic view which only shows the facts (i.e. triples) stated in the text. RDFaCE provides a syncronization between these four views so that changes in one view cause respective changes in the other views.

Another important RDFaCE feature is the combining of results from multiple NLP APIs to facilitate the semantic authoring process with automatic annotations. This feature provides an initial set of annotations for users that can be modified and extended later on.

A demo version of RDFaCE is available at http://rdface.aksw.org. To see a short screencast of RDFaCE features, visit here. For more information visit the RDFaCE Project Page.

We could not resist the pleasure of making the demo of the new release candidate of LIMES (0.5RC1) available for all. LIMES 0.5 comes fitted with a new grammar for complex metric specification and fully novel algorithms. The new version of our framework scales even better than the previous ones and is several order of magnitude faster than other Link Discovery Frameworks. We are currently cleaning the code and adding some more features here and there. Stay tuned for the upcoming release. More information on the project and a demo can be accessed at http://limes.sf.net.

Link on!
Axel