Classifier Instance:

Anchor text: Huffman coding
Target Entity: Huffman_coding
Preceding Context: #
Succeeding Context: : this process replaces fixed length symbols in the range 0–258 with variable length codes based on the frequency of use. More frequently used codes end up shorter (2-3 bits) whilst rare codes can be allocated up to 20 bits. The codes are selected carefully so that no sequence of bits can be confused for a different code. The end-of-stream code is particularly interesting. If there are n different bytes (symbols) used in the uncompressed data, then the Huffman code will consist of two RLE codes (RUNA and RUNB), n-1 symbol codes and one end-of-stream code. Because of the combined result of the MTF and RLE encodings in the previous two steps, there is never any need to explicitly reference the first symbol in the MTF table, thus saving one symbol for the end-of-stream marker (and explaining why only n-1 symbols are coded in the Huffman tree). In the extreme case where only one symbol is used in the uncompressed data, there will be no symbol codes at all in the Huffman tree, and the entire block will consist of RUNA and RUNB (implicitly repeating the single byte) and an end-of-stream marker with value 2.
Paragraph Title: null
Source Page: Bzip2

Ground Truth Types:

|---wordnet_entity_100001740
|  |---wordnet_event_100029378
|  |  |---wordnet_act_100030358
|  |  |  |---wordnet_activity_100407535
|  |  |  |  |---wordnet_procedure_101023820
|  |  |  |  |  |---wordnet_rule_105846932
|  |  |  |  |  |  |---wordnet_algorithm_105847438

Predicted Types:

TypeConfidenceDecision
wordnet_artifact_100021939-2.7230478063228905 0
wordnet_event_1000293780.5240711094539006 1
wordnet_act_1000303582.9387726399899923 1
wordnet_action_100037396-1.809204134871076 0
wordnet_activity_1004075352.731264711724782 1
wordnet_game_100455599-1.763951598841166 0
wordnet_diversion_100426928-2.1057820885766123 0
wordnet_representation_100898518-2.4144121571586363 0
wordnet_use_100947128-2.045339446530234 0
wordnet_wrongdoing_100732746-1.5868666223904866 0
wordnet_procedure_1010238201.847560367069918 1
wordnet_rule_1058469321.8638759098821984 1
wordnet_algorithm_1058474381.4951514326356248 1
wordnet_work_100575741-1.776223678362109 0
wordnet_sensory_activity_100876737-1.7064247675188824 0
wordnet_operation_100955060-1.2134333393468506 0
wordnet_occupation_100582388-1.8237432408147205 0
wordnet_speech_act_107160883-1.9202980992623848 0
wordnet_group_action_101080366-2.4299162361547295 0
wordnet_communication_106252138-1.9196686856244771 0
wordnet_social_event_107288639-2.938780311336842 0
wordnet_happening_107283608-1.9624862389750215 0
wordnet_group_action_101080366-2.0923740790858045 0
wordnet_organization_108008335-3.244773642216652 0
wordnet_person_100007846-2.35480989523574 0
yagoGeoEntity-3.473019358265468 0
|---wordnet_entity_100001740
|  |---wordnet_artifact_100021939
|  |---wordnet_event_100029378
|  |  |---wordnet_act_100030358
|  |  |  |---wordnet_action_100037396
|  |  |  |---wordnet_activity_100407535
|  |  |  |  |---wordnet_game_100455599
|  |  |  |  |---wordnet_diversion_100426928
|  |  |  |  |---wordnet_representation_100898518
|  |  |  |  |---wordnet_use_100947128
|  |  |  |  |---wordnet_wrongdoing_100732746
|  |  |  |  |---wordnet_procedure_101023820
|  |  |  |  |  |---wordnet_rule_105846932
|  |  |  |  |  |  |---wordnet_algorithm_105847438
|  |  |  |  |---wordnet_work_100575741
|  |  |  |  |---wordnet_sensory_activity_100876737
|  |  |  |  |---wordnet_operation_100955060
|  |  |  |  |---wordnet_occupation_100582388
|  |  |  |---wordnet_speech_act_107160883
|  |  |  |---wordnet_group_action_101080366
|  |  |  |---wordnet_communication_106252138
|  |  |---wordnet_social_event_107288639
|  |  |---wordnet_happening_107283608
|  |  |---wordnet_group_action_101080366
|  |---wordnet_organization_108008335
|  |---wordnet_person_100007846
|  |---yagoGeoEntity