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FreeLing
4.0
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The class bioner implements an AdaBoost-Based NE recognizer. More...
#include <bioner.h>


Public Member Functions | |
| bioner (const std::wstring &) | |
| Constructor. | |
| ~bioner () | |
| Destructor. | |
| void | SetMultiwordAnalysis (sentence::iterator) const |
| void | analyze (sentence &) const |
| Recognize NEs in given sentence. | |
Private Attributes | |
| const fex * | extractor |
| feature extractor | |
| const classifier * | classif |
| adaboost classifier | |
| vis_viterbi | vit |
| Viterbi solver. | |
The class bioner implements an AdaBoost-Based NE recognizer.
| freeling::bioner::bioner | ( | const std::wstring & | nerFile | ) |
Constructor.
Perform named entity recognition using AdaBoost.
Create a named entity recognition module, loading appropriate files.
References freeling::util::absolute(), freeling::config_file::add_section(), classif, freeling::config_file::close(), ERROR_CRASH, extractor, freeling::nerc_features::functions, freeling::config_file::get_content_line(), freeling::config_file::get_section(), freeling::util::lowercase(), freeling::config_file::open(), and TRACE.
| void freeling::bioner::analyze | ( | sentence & | se | ) | const [virtual] |
Recognize NEs in given sentence.
Reimplemented from freeling::automat< ner_status >.
References freeling::example::add_feature(), freeling::ner_module::BuildMultiword(), classif, freeling::classifier::classify(), freeling::fex::encode_int(), extractor, freeling::vis_viterbi::find_best_path(), freeling::classifier::get_index(), freeling::classifier::get_label(), freeling::classifier::get_nlabels(), int2wstring, freeling::sentence::rebuild_word_index(), TRACE, TRACE_SENTENCE, and vit.
| void freeling::bioner::SetMultiwordAnalysis | ( | sentence::iterator | ) | const |
const classifier* freeling::bioner::classif [private] |
const fex* freeling::bioner::extractor [private] |
vis_viterbi freeling::bioner::vit [private] |
Viterbi solver.
Referenced by analyze().
1.7.6.1