Classifier Instance:

Anchor text: MIM-72 Chaparral
Target Entity: MIM\u002d72_Chaparral
Preceding Context: By the beginning of December, Israel had received between 34 to 40 F-4 fighter-bombers, 46 A-4 attack airplanes, 12 C-130 cargo airplanes, 8 CH-53 helicopters, 40 unmanned aerial vehicles, 200 M-60/M-48A3 tanks, 250 armored personnel carriers, 226 utility vehicles, 12
Succeeding Context: surface-to-air missile systems, 3 MIM-23 Hawk surface-to-air missile systems, 36 155 mm artillery pieces, 7 175 mm artillery pieces, large quantities of 105 mm, 155 mm and 175 mm ammunition, state of the art equipment, such as the AGM-65 Maverick missile and the BGM-71 TOW, weapons that had only entered production one or more years prior, as well as highly advanced electronic jamming equipment.
Paragraph Title: null
Source Page: Yom Kippur War

Ground Truth Types:

|---wordnet_entity_100001740
|  |---wordnet_artifact_100021939
|  |  |---wordnet_instrumentality_103575240
|  |  |  |---wordnet_conveyance_103100490
|  |  |  |  |---wordnet_vehicle_104524313
|  |  |  |  |  |---wordnet_vehicle_104524313_rest
|  |  |  |---wordnet_device_103183080
|  |  |  |  |---wordnet_instrument_103574816
|  |  |  |  |  |---wordnet_weapon_104565375
|  |  |  |  |  |  |---wordnet_weapon_104565375_rest

Predicted Types:

TypeConfidenceDecision
wordnet_artifact_1000219393.041538504858678 1
wordnet_instrumentality_1035752404.492671258802882 1
wordnet_conveyance_1031004902.0554170011153556 1
wordnet_vehicle_1045243132.8919949411429102 1
wordnet_military_vehicle_103764276-2.4026264885905753 0
wordnet_craft_103125870-3.1966537989868877 0
wordnet_wheeled_vehicle_104576211-1.244092373405619 0
wordnet_medium_106254669-3.625473889045253 0
wordnet_device_1031830801.476884576512694 1
wordnet_instrument_1035748162.6750892874181376 1
wordnet_weapon_1045653752.314134217941879 1
wordnet_gun_103467984-1.8520023666826368 0
wordnet_memory_device_103744840-1.900688747276525 0
wordnet_machine_103699975-2.945673481138614 0
wordnet_mechanism_103738472-2.2312398082537457 0
wordnet_musical_instrument_103800933-2.7233534889316955 0
wordnet_container_103094503-1.9104002542102911 0
wordnet_equipment_103294048-2.1856843827615946 0
wordnet_system_104377057-2.5455731313690917 0
wordnet_structure_104341686-3.292130802470655 0
wordnet_facility_103315023-2.993890464850712 0
wordnet_creation_103129123-4.989566027926453 0
wordnet_article_100022903-3.7416243910115052 0
wordnet_commodity_103076708-1.488132787365099 0
wordnet_way_104564698-4.325421633754149 0
wordnet_covering_103122748-3.2597897621023635 0
wordnet_event_100029378-3.7310224446472833 0
wordnet_organization_108008335-2.7718626401348843 0
wordnet_person_100007846-4.3638722240762275 0
yagoGeoEntity-1.95726577506951 0
|---wordnet_entity_100001740
|  |---wordnet_artifact_100021939
|  |  |---wordnet_instrumentality_103575240
|  |  |  |---wordnet_conveyance_103100490
|  |  |  |  |---wordnet_vehicle_104524313
|  |  |  |  |  |---wordnet_military_vehicle_103764276
|  |  |  |  |  |---wordnet_craft_103125870
|  |  |  |  |  |---wordnet_wheeled_vehicle_104576211
|  |  |  |---wordnet_medium_106254669
|  |  |  |---wordnet_device_103183080
|  |  |  |  |---wordnet_instrument_103574816
|  |  |  |  |  |---wordnet_weapon_104565375
|  |  |  |  |  |  |---wordnet_gun_103467984
|  |  |  |  |---wordnet_memory_device_103744840
|  |  |  |  |---wordnet_machine_103699975
|  |  |  |  |---wordnet_mechanism_103738472
|  |  |  |  |---wordnet_musical_instrument_103800933
|  |  |  |---wordnet_container_103094503
|  |  |  |  |---wordnet_wheeled_vehicle_104576211
|  |  |  |---wordnet_equipment_103294048
|  |  |  |---wordnet_system_104377057
|  |  |---wordnet_structure_104341686
|  |  |---wordnet_facility_103315023
|  |  |---wordnet_creation_103129123
|  |  |---wordnet_article_100022903
|  |  |---wordnet_commodity_103076708
|  |  |---wordnet_way_104564698
|  |  |---wordnet_covering_103122748
|  |---wordnet_event_100029378
|  |---wordnet_organization_108008335
|  |---wordnet_person_100007846
|  |---yagoGeoEntity
|  |  |---wordnet_structure_104341686
|  |  |---wordnet_facility_103315023
|  |  |---wordnet_way_104564698