Annotators and Consumers

• Whitespace Tokenizer Annotator
• Snowball Annotator
• Regular Expression Annotator
• Dictionary Annotator
• Hidden Markov Model Tagger Annotator
• BSF Annotator
• OpenCalais Annotator
• Concept Mapper Annotator
• Configurable Feature Extractor Annotator
• Tika Annotator
• Lucene CAS indexer (Lucas)
• AlchemyAPI Annotator
• Solr CAS Consumer (Solrcas)

Servers

• Simple Server (UIMA REST service)

Packaging tools

• PEAR Packaging ANT Task
• PEAR Packaging Maven Plugin

Miscellaneous

• Feature Structure Variables

These are described in more detail below.

Snowball Annotator

The Snowball annotator is an UIMA annotator component that wraps the Snowball stemming algorithm. The annotator iterates over the available token annotations in the CAS and creates for each token a feature containing the stem. The stemming algorithm is avaialble for several languages. For details about Snowball please see https://snowball.tartarus.org/. The Java source of the annotator can be accessed in the SVN repository at https://svn.apache.org/repos/asf/uima/addons/trunk/SnowballAnnotator. Note: the used implementation of the Snowball stemming algorithm is licensed under the BSD license.

Hidden Markov Model Tagger Annotator

The Tagger Annotator component implements a Hidden Markov Model (HMM) tagger. The tagger assumes that sentences and tokens have already been annotated in the CAS with sentence and token annotations. It iterates then in turn over sentences and tokens to accumulate a list of words, and then invokes the tagger on this list. The HMM tagger employs the Viterbi algorithm to calculate the most probable tag sequence. For each Token it updates the posTag field with the part of speech tag. Model training is happening outside of UIMA, the tagger just receives statistical information from a model file which is passed to the tagger along with some further parameters through a properties file. Click here to access the user documentation. The Java source of the annotator can be accessed in the SVN repository at https://svn.apache.org/repos/asf/uima/addons/trunk/Tagger.

Tika Annotator

Apache Tika is a toolkit for detecting and extracting metadata and structured text content from various documents using existing parser libraries. The TikaAnnotator uses Tika to generate annotations representing the original markup of a document, extract its text and metadata. It consists of three resources: FileSystemCollectionReader similar to the one in UIMA examples but uses TIKA to extract the text from binary documents and generates annotations to represent the markup MarkupAnnotator takes the original content from a view and generates a new view containing the extracted text with markup annotations TikaWrapper utility class which allows to populate a CAS from a binary document; used by the FileSystemCollectionReader

Lucene CAS indexer (Lucas)

The Lucene CAS indexer (Lucas) is a UIMA CAS consumer that stores CAS data in a Lucene index. The consumer transforms annotation objects of a CAS into Lucene token streams which are stored in a Lucene document. Token streams can further be processed by token filters. Lucas comes with a set of its own token filters and integrations for some Lucene token filters. Furthermore, you can deploy your own token filters. The mapping between UIMA annotations and Lucene tokens and token filtering is configured by a xml mapping file. Click here to access the user documentation. The Java source of the consumer can be accessed in the SVN repository.

OpenCalais Annotator

The OpenCalais Annotator component wraps the OpenCalais web service and makes the OpenCalais analysis results available in UIMA. OpenCalais can detect a large variety of entities, facts and events like for example Persons, Companies, Acquisitions, Mergers, etc. For details about the OpenCalais analytics and the license to use the service, please refer to the to the OpenCalais website. The Java source of the annotator can be accessed in the SVN repository at https://svn.apache.org/repos/asf/uima/addons/trunk/OpenCalaisAnnotator.

Concept Mapper Annotator

ConceptMapper is a powerful, highly configurable dictionary UIMA-based annotator. Numerous parameters can be used to specify various aspects of the lookup algorithm, input processing and output options. The dictionary structure is flexible, allowing any number synonyms to be associated with an entry, and any number of attributes to be associated with entries or synonyms. ConceptMapper is separately released, and available on the downloads page. Lookup and matching against dictionary entries can be performed against contiguous or non-contiguous blocks of text, and token order independent lookup is also allowed (for example, the tokens "A" "B" would be considered a match against dictionary entry "B" "A"). Additionally, ConceptMapper can be configured to use any tokenizer annotator, enabling tokenization of the dictionary identically with the input text. Click here to access the user documentation.

Configurable Feature Extractor Annotator

The Configurable Feature Extractor (CFE) Annotator is a multipurpose tool that enables feature extraction from a UIMA CAS in a very generalized and application independent way. The extraction process is performed according to rules expressed using the Feature Extraction Specification Language (FESL) that are stored in configuration files. Using CFE eliminates the need for creating customized CAS consumers and writing Java code for every application. Instead, by using FESL rules in XML format, users can customize the information extraction process to suit their application. FESL's rule semantics allow the precise identification of the information that is required to be extracted by specifying precise multi-parameter criteria. Click here to access the user documentation.