Common Pattern Specific Language) is based on the TIPSTER annotation format (Grishman, 1997). Based on an external linguistic annotation platform, namely GATE, the KIM platform (Popov et al., 2004) can be considered as a "meta-platform". It is designed for ontology population, semantic indexing and information retrieval. KIM has been integrated in massive semantic annotation projects such as the SWAN clusters 1 and SEKT.

2 The authors identify scalability as a critical parameter for two reasons: (1) it has to be able to process large amounts of data, in order to build and train statistical models for Information Extraction; (2) it has to support its own use as an online public service. UIMA (Furrucci & Lally, 2004), a new implementation architecture of TEXTRACT (Neff et al., 2004), is similar to GATE. It mainly differs from GATE in the data representation model. UIMA is a framework for the development of analysis engines. It offers components for the analysis of unstructured information streams as HTML web pages. These components are supposed to range from lightweight to highly scalable implementations. The UIMA SDK is a collection of Java classes. The UIMA annotation format is called CAS (Common Analysis Structure). It is mainly based on the TIPSTER format (Grishman, 1997). CAS annotations are stand-off for the sake of flexibility. Documents can be processed either at a single document level or at a collection level. Collections are handled in UIMA by the Collection Processing Engine, which has some interesting features such as filtering, performance monitoring and parallelization.

The Textpresso system (Muller et al., 2004) has been specifically developed to mine biological documents, abstracts as well as articles. For instance, it has been used to process 16,000 abstracts and 3,000 full text articles related to Caenorhabditis *elegans*. It is designed as a curation system extracting gene-gene interaction that is also used as a search engine. It integrates the following NLP modules: tokenizer, sentence segmentation, Part-Of-Speech (POS) tagging, and an semantic tagging based on Gene Ontology (GOConsortium, 2001). While Textpresso is specifically designed for biomedical texts, our platform is more similar to GATE in its aim: proposing a generic platform to process large document collections. Generally, very little information is given to evaluate the behavior of the systems on a collection of documents whereas from our point of view, this aspect is crucial for such a system. Our first test shows that GATE is not suited to process large collections of documents. GATE has been designed as a powerful environment for conception and development of NLP applications in information extraction. Scalability is not central in its design, and information extraction deals with small sets of documents. However, we have observed that problems appear on small sets of documents. We choose to propose a platform able to analyze large amounts of documents, and focus on the efficiency of the processing.

## 3. A Modular And Tunable Platform

In the development of Ogmios, we focused on tool integration. Our initial goal was to exploit existing NLP tools rather than developing new ones 3 but integrating heterogeneous tools and nevertheless achieve good performance in document annotation was challenging. Ogmios platform was designed to test various combinations of annotations in order to identify which 1 http://deri.ie/projects/swan 2 http://sekt.semanticweb.org 3 We developed NLP systems only when no other solution was available. We preferably chose GPL or free licence software when possible.