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{{Wiki_List |
A full week of learning [http://en.wikipedia.org/wiki/General_Architecture_for_Text_Engineering GATE] text mining/information extraction language processing and talks. [http://gate.ac.uk/wiki/TrainingCourseAug2010/ Session wiki]
wiki_name  =                ConsumeriumWiki                                        |
 
wiki_logo =                  [[Image:NoLogo.png]]                                  |
[[File:GATE_screenshot.png|900px|GATE developer screenshot]]
wiki_URL =                  http://develop.consumerium.org/wiki/index.php                                                    |
 
wiki_recentchanges =       No                                                                                                |
GATE is written in Java and very Java centric. This makes it portable, fast, and heavyweight. A programming library is available.  It's 14 years old and has many users and contributors.
wiki_status =               Inactive                  |
 
wiki_lastreviewed =       16-Jan-06                  |
= Using GATE developer =
wiki_language =             Unknown                  |
 
wiki_editmode =             OpenEdit            |
* GATE developer is used to process sets of Language Resources in Corpus using Processing Resources. They are typically saved to a serialized Datastore.
wiki_engine =               Unknown                        |
* ANNIE, VG (verb group) processors.
wiki_maintopic =           Defunct
* Preserve formatting embeds tags in HTML or XML.
}}
** Different strengths using GATE's graph (node/offset) based XML vs. preserved formatting (original xml/html)
==Description==
 
Not Found
= Information Extraction =
 
* IR - retrieve docs
* IE - retreive structured data
 
* Knowledge Engineering - rule based
* Learning Systems - statistical
 
Old Bailey IE project - old english (Online)
 
* POS - assigned in Token (noun, verb, etc)
 
* Gazateer - gotcha, have to set initialization parameter listsURL before it's
loaded. Must also "save and reinitialize."
* Gazeteer creates Lookups, then transducer creaties named entities
* Then orthomatcher (spelling features in common) coreference associates those
 
* Annotation Key sets and annotation comparing
** Need setToKeep key in Document Reset for any pre annotated texts
 
== Evaluation / Metrics ==
 
* Evaluation metric - mathematically against human annotated
* Scoring - performance measures for annotation types
 
* Result types - Correct, missing, spurious, partially correct (overlapped)
 
* Tools > Annotations Diff - comparing human vs machine annotation
 
* Corpus > Corpus quality assurance - compare by type
* (B has to be the generated set)
 
* Annotation set transfer (in tools) - transfer between docs in pipeline
** useful for eg HTML that has boilerplate
 
= Other notes =
 
== Lucene data store ==
 
* Use <null> for default set
* Go to Datastore for queries
** eg {Person}({Token})+{Money}
 
[[File:GATE-lucene-person-money.png]]
 
== To investigate ==
 
* markupAware for HTML/XML (keeps tags in editor)
* AnnotationStack
* Advanced Options
 
= JAPE =
 
* Rules based on tokens and lookups
 
== To review, gotchas ==
 
* Rule types : first takes only first match, excludes compound
** a? b for "a b" will match "a b"
* multiplexor tranducers
* multi-constraint statements
* macros
* To reuse created annotations has to be a separate rule
 
= To follow up =
 
* WebSphinx crawler CREOLE plugin
 
= Conclusions =
 
While it can do a lot out of the box and benefits from development time and breadth of connectivity, it needs usability testing, a lot of things are inobvious and too domain specific. It could really use some "sexying up," interaction could including a lot more useful and interesting looking displays. A web based version could have these features.
 
{{Blikied|Aug 30, 2010}}
 
[[Category:SemWeb]]

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