Introduction to ANNIE

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Introduction to ANNIE
http//gate.ac.uk/ http//nlp.shef.ac.uk/

• Diana Maynard
• University of Sheffield
• March 2004

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What is ANNIE?

• ANNIE is a vanilla information extraction system
  comprising a set of core PRs
• Tokeniser
• Sentence Splitter
• POS tagger
• Gazetteers
• Semantic tagger (JAPE transducer)
• Orthomatcher (orthographic coreference)

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ANNIE Pipeline
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Other Processing Resources

• There are also lots of additional processing
  resources which are not part of ANNIE itself but
  which come with the default installation of GATE
• Gazetteer collector
• PRs for Machine Learning
• Various exporters
• Annotation set transfer
• etc.

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Creating a new application from ANNIE

• Typically a new application will use most of the
  core components from ANNIE
• The tokeniser, sentence splitter and orthomatcher
  are basically language, domain and
  application-independent
• The POS tagger is language dependent but domain
  and application-independent
• The gazetteer lists and JAPE grammars may act as
  a starting point but will almost certainly need
  to be modified
• You may also require additional PRs (either
  existing or new ones)

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Modifying gazetteers

• Gazetteers are plain text files containing lists
  of names
• Each gazetteer set has an index file listing all
  the lists, plus features of each list (majorType,
  minorType and language)
• Lists can be modified either internally using
  Gaze, or externally in your favourite editor
• Gazetteers can also be mapped to ontologies
• To use Gaze and the ontology editor, you need to
  download the relevant creole files

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JAPE grammars

• A semantic tagger consists of a set of rule-based
  JAPE grammars run sequentially
• JAPE is a pattern-matching language
• The LHS of each rule contains patterns to be
  matched
• The RHS contains details of annotations (and
  optionally features) to be created
• More complex rules can also be created

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Input specifications

• The head of each grammar phase needs to contain
  certain information
• Phase name
• Inputs
• Matching style
• e.g.
• Phase location
• Input Token Lookup Number
• Control appelt

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Matching algorithms and Rule Priority

• 3 styles of matching
• Brill (fire every rule that applies)
• First (shortest rule fires)
• Appelt (use of priorities)
• Appelt priority is applied in the following order
• Starting point of a pattern
• Longest pattern
• Explicit priority (default -1)

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NE Rule in JAPE Rule Company1 Priority 25
( ( Token.orthography
upperInitial ) //from tokeniser
Lookup.kind companyDesignator //from
gazetteer lists )match --gt
match.NamedEntity kindcompany,
ruleCompany1
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LHS of the rule

• LHS is expressed in terms of existing
  annotations, and optionally features and their
  values
• Any annotation to be used must be included in the
  input header
• Any annotation not included in the input header
  will be ignored (e.g. whitespace)
• Each annotation is enclosed in curly braces
• Each pattern to be matched is enclosed in round
  brackets and has a label attached

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Macros

• Macros look like the LHS of a rule but have no
  label
• Macro NUMBER
• ((Digit))
• They are used in rules by enclosing the macro
  name in round brackets
• ( (NUMBER))match
• Conventional to name macros in uppercase letters
• Macros hold across an entire set of grammar phases

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Contextual information

• Contextual information can be specified in the
  same way, but has no label
• Contextual information will be consumed by the
  rule
• (Annotation1)
• (Annotation2)match
• (Annotation3)
• ?

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RHS of the rule

• LHS and RHS are separated by ?
• Label matches that on the LHS
• Annotation to be created follows the label
• (Annotation1)match
• ? match.NE feature1 value1, feature2
  value2

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Using phases

• Grammars usually consist of several phases, run
  sequentially
• Only one rule within a single phase can fire
• Temporary annotations may be created in early
  phases and used as input for later phases
• Annotations from earlier phases may need to be
  combined or modified
• A definition phase (conventionally called
  main.jape) lists the phases to be used, in order
• Only the definition phase needs to be loaded

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More complex JAPE rules

• Any Java code can be used on the RHS of a rule
• This is useful for e.g. feature percolation,
  ontology population, accessing information not
  readily available, comparing feature values,
  deleting existing annotations etc.
• There are examples of these in the user guide and
  in the ANNIE NE grammars
• Most JAPE rules end up being complex!

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Using JAPE for other tasks

• JAPE grammars are not just useful for NE
  annotation
• They can be a quick and easy way of performing
  any kind of task where patterns can be easily
  recognised and a finite-state approach is
  possible, e.g. transforming one style of markup
  into another, deriving features for the learning
  algorithms

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Example rule for deriving features

• Rule Entity( Gpe Organization
  Person Location Facility
• )entity--gtgate.AnnotationSet entityAS
• (gate.AnnotationSet)bindings.get("entity")
• gate.Annotation entityAnn (gate.Annotation)entit
  yAS.iterator().next()
• gate.FeatureMap features Factory.newFeatureMap()
  
• features.put("type", entityAnn.getType())outputA
  S.add(entityAnn.getStartNode(),
  entityAnn.getEndNode(),
• "Entity, features)

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Finding Examples

• ANNIE for default NE rules
• gate/src/gate/resources/creole/NEtransducer/NE/
• MUSE for more complex NE rules
• muse/src/muse/resources/grammar/main
• h-TechSight for ontology population
• htechsight/application/grammar
• Various other applications generally follow the
  format
• projectname/application/grammar/

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Conclusion

• This talk http//gate.ac.uk/sale/talks/annie-tut
  orial.ppt
• More information http//gate.ac.uk/