Classifier Instance:

Anchor text: Poisson process
Target Entity: Poisson_process
Preceding Context: A useful queueing model represents a real-life system with sufficient accuracy and is analytically tractable. A queueing model based on the
Succeeding Context: and its companion exponential probability distribution often meets these two requirements. A Poisson process models random events (such as a customer arrival, a request for action from a web server, or the completion of the actions requested of a web server) as emanating from a memoryless process. That is, the length of the time interval from the current time to the occurrence of the next event does not depend upon the time of occurrence of the last event. In the Poisson probability distribution, the observer records the number of events that occur in a time interval of fixed length. In the (negative) exponential probability distribution, the observer records the length of the time interval between consecutive events. In both, the underlying physical process is memoryless.
Paragraph Title: Role of Poisson process, exponential distributions
Source Page: Queueing theory

Ground Truth Types:

|---wordnet_entity_100001740
|  |---wordnet_event_100029378
|  |  |---wordnet_act_100030358
|  |  |  |---wordnet_activity_100407535
|  |  |  |  |---wordnet_procedure_101023820
|  |  |  |  |  |---wordnet_procedure_101023820_rest

Predicted Types:

TypeConfidenceDecision
wordnet_artifact_100021939-2.3721365915689705 0
wordnet_event_1000293781.006700300772755 1
wordnet_act_1000303581.4363777136200553 1
wordnet_action_100037396-2.400679205565807 0
wordnet_activity_1004075351.1008083325973337 1
wordnet_game_100455599-2.1709479793857374 0
wordnet_diversion_100426928-1.4139296205067229 0
wordnet_representation_100898518-2.0797164597730506 0
wordnet_use_100947128-1.3000921999335457 0
wordnet_wrongdoing_100732746-1.2650774466823143 0
wordnet_procedure_1010238201.7424558198854996 1
wordnet_rule_105846932-1.4989636936256843 0
wordnet_work_100575741-1.4505861963374076 0
wordnet_sensory_activity_100876737-1.3288983906394214 0
wordnet_operation_100955060-1.634860739186959 0
wordnet_occupation_100582388-1.4559848669730961 0
wordnet_speech_act_107160883-1.6703578954913834 0
wordnet_group_action_101080366-1.768677910708477 0
wordnet_communication_106252138-1.8185148711127614 0
wordnet_social_event_107288639-2.5034125300235184 0
wordnet_happening_107283608-1.5794197960682146 0
wordnet_group_action_101080366-2.0402227151865064 0
wordnet_organization_108008335-2.60790176556376 0
wordnet_person_100007846-1.4218410214261974 0
yagoGeoEntity-2.378469929896987 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_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