WordNet是面向语义的英语词典，与传统辞典类似，但结构更丰富。nltk中包括英语WordNet，共有155287个单词和117659个同义词。
1.寻找同义词
这里以motorcar为例，寻找它的同义词集。
1 >>> from nltk.corpus import wordnet as wn 2 >>> wn.synsets(‘motorcar‘) //找到同义词集 3 [Synset(‘car.n.01‘)] 4 >>> wn.synset(‘car.n.01‘).lemma_names 5 <bound method Synset.lemma_names of Synset(‘car.n.01‘)> 6 >>> wn.synset(‘car.n.01‘).lemma_names() //访问同义词集 7 [‘car‘, ‘auto‘, ‘automobile‘, ‘machine‘, ‘motorcar‘] 8 >>>
1 >>> wn.synset(‘car.n.01‘).definition() //获取该词在该词集的定义 2 ‘a motor vehicle with four wheels; usually propelled by an internal combustion engine‘ 3 >>> wn.synset(‘car.n.01‘).examples() //获取该词在该词集下的例句 4 [‘he needs a car to get to work‘] 5 >>> wn.synset(‘car.n.01‘).lemmas() 6 [Lemma(‘car.n.01.car‘), Lemma(‘car.n.01.auto‘), Lemma(‘car.n.01.automobile‘), Lemma(‘car.n.01.machine‘), Lemma(‘car.n.01.motorcar‘)] 7 >>> wn.lemma(‘car.n.01.automobile‘) 8 Lemma(‘car.n.01.automobile‘) 9 >>> wn.lemma(‘car.n.01.automobile‘).synset() 10 Synset(‘car.n.01‘) 11 >>> wn.lemma(‘car.n.01.automobile‘).name() 12 ‘automobile‘ 13 >>> wn.synsets(‘car‘) 14 [Synset(‘car.n.01‘), Synset(‘car.n.02‘), Synset(‘car.n.03‘), Synset(‘car.n.04‘), Synset(‘cable_car.n.01‘)] 15 >>> for synset in wn.synsets(‘car‘): 16 ... print (synset.lemma_names()) 17 ... 18 [‘car‘, ‘auto‘, ‘automobile‘, ‘machine‘, ‘motorcar‘] 19 [‘car‘, ‘railcar‘, ‘railway_car‘, ‘railroad_car‘] 20 [‘car‘, ‘gondola‘] 21 [‘car‘, ‘elevator_car‘] 22 [‘cable_car‘, ‘car‘] 23 >>> wn.lemmas(‘car‘) //访问所有包含词car的词条 24 [Lemma(‘car.n.01.car‘), Lemma(‘car.n.02.car‘), Lemma(‘car.n.03.car‘), Lemma(‘car.n.04.car‘), Lemma(‘cable_car.n.01.car‘)] 25 >>>
2.WordNet的层次结构
WordNet的同义词集相当于抽象的概念，它们并不总是有对应的英语词汇。这些概念在层次结构中相互联系在一起。
如上图，是WordNet概念的层次片段。每个节点对应一个同义词集，边表示上位词/下位词关系，即上级概念与从属概念的关系。
1 >>> motorcar=wn.synset(‘car.n.01‘) 2 >>> types_of_motorcar=motorcar.hyponyms() 3 >>> types_of_motorcar[26] 4 Synset(‘stanley_steamer.n.01‘) 5 >>> sorted( 6 ... [lemma.name() 7 ... for synset in types_of_motorcar 8 ... for lemma in synset.lemmas()]) 9 [‘Model_T‘, ‘S.U.V.‘, ‘SUV‘, ‘Stanley_Steamer‘, ‘ambulance‘, ‘beach_waggon‘, ‘beach_wagon‘, ‘bus‘, ‘cab‘, ‘compact‘, ‘compact_car‘, ‘convert 10 ible‘, ‘coupe‘, ‘cruiser‘, ‘electric‘, ‘electric_automobile‘, ‘electric_car‘, ‘estate_car‘, ‘gas_guzzler‘, ‘hack‘, ‘hardtop‘, ‘hatchback‘, ‘ 11 heap‘, ‘horseless_carriage‘, ‘hot-rod‘, ‘hot_rod‘, ‘jalopy‘, ‘jeep‘, ‘landrover‘, ‘limo‘, ‘limousine‘, ‘loaner‘, ‘minicar‘, ‘minivan‘, ‘pace 12 _car‘, ‘patrol_car‘, ‘phaeton‘, ‘police_car‘, ‘police_cruiser‘, ‘prowl_car‘, ‘race_car‘, ‘racer‘, ‘racing_car‘, ‘roadster‘, ‘runabout‘, ‘sal 13 oon‘, ‘secondhand_car‘, ‘sedan‘, ‘sport_car‘, ‘sport_utility‘, ‘sport_utility_vehicle‘, ‘sports_car‘, ‘squad_car‘, ‘station_waggon‘, ‘statio 14 n_wagon‘, ‘stock_car‘, ‘subcompact‘, ‘subcompact_car‘, ‘taxi‘, ‘taxicab‘, ‘tourer‘, ‘touring_car‘, ‘two-seater‘, ‘used-car‘, ‘waggon‘, ‘wago 15 n‘] 16 >>> motorcar.hypernyms() 17 [Synset(‘motor_vehicle.n.01‘)] 18 >>> paths=motorcar.hypernym_paths() 19 >>> len(paths) 20 2 21 >>> [synset.name for synset in paths[0]] 22 [<bound method Synset.name of Synset(‘entity.n.01‘)>, <bound method Synset.name of Synset(‘physical_entity.n.01‘)>, <bound method Synset.nam 23 e of Synset(‘object.n.01‘)>, <bound method Synset.name of Synset(‘whole.n.02‘)>, <bound method Synset.name of Synset(‘artifact.n.01‘)>, <bou 24 nd method Synset.name of Synset(‘instrumentality.n.03‘)>, <bound method Synset.name of Synset(‘container.n.01‘)>, <bound method Synset.name 25 of Synset(‘wheeled_vehicle.n.01‘)>, <bound method Synset.name of Synset(‘self-propelled_vehicle.n.01‘)>, <bound method Synset.name of Synset 26 (‘motor_vehicle.n.01‘)>, <bound method Synset.name of Synset(‘car.n.01‘)>] 27 >>> [synset.name() for synset in paths[0]] 28 [‘entity.n.01‘, ‘physical_entity.n.01‘, ‘object.n.01‘, ‘whole.n.02‘, ‘artifact.n.01‘, ‘instrumentality.n.03‘, ‘container.n.01‘, ‘wheeled_veh 29 icle.n.01‘, ‘self-propelled_vehicle.n.01‘, ‘motor_vehicle.n.01‘, ‘car.n.01‘] 30 >>> [synset.name() for synset in paths[1]] 31 [‘entity.n.01‘, ‘physical_entity.n.01‘, ‘object.n.01‘, ‘whole.n.02‘, ‘artifact.n.01‘, ‘instrumentality.n.03‘, ‘conveyance.n.03‘, ‘vehicle.n. 32 01‘, ‘wheeled_vehicle.n.01‘, ‘self-propelled_vehicle.n.01‘, ‘motor_vehicle.n.01‘, ‘car.n.01‘] 33 >>> motorcar.root_hypernyms() 34 [Synset(‘entity.n.01‘)] 35 >>>
3.更多的词汇关系
上位词和下位词被称为词汇关系，因为它们是同义集之间的关系。这两者的关系为上下定位“is-a”层次。WordNet网络另一个重要的定位方式是从条目到它们的部件（部分）或到包含它们的东西（整体）。
1）部分-整体关系
1 >>> wn.synset(‘tree.n.01‘).part_meronyms() 2 [Synset(‘burl.n.02‘), Synset(‘crown.n.07‘), Synset(‘limb.n.02‘), Synset(‘stump.n.01‘), Synset(‘trunk.n.01‘)] 3 >>> wn.synset(‘tree.n.01‘).substance_meronyms() 4 [Synset(‘heartwood.n.01‘), Synset(‘sapwood.n.01‘)] 5 >>> wn.synset(‘tree.n.01‘).member_holonyms() 6 [Synset(‘forest.n.01‘)] 7 >>> for synset in wn.synsets(‘mint‘, wn.NOUN): 8 ... print("%s : %s" % (synset.name(), synset.definition()) 9 ... 10 ... 11 ... ) 12 ... 13 batch.n.02 : (often followed by `of‘) a large number or amount or extent 14 mint.n.02 : any north temperate plant of the genus Mentha with aromatic leaves and small mauve flowers 15 mint.n.03 : any member of the mint family of plants 16 mint.n.04 : the leaves of a mint plant used fresh or candied 17 mint.n.05 : a candy that is flavored with a mint oil 18 mint.n.06 : a plant where money is coined by authority of the government 19 >>> wn.synset(‘mint.n.04‘).part_holonyms() 20 [Synset(‘mint.n.02‘)] 21 >>> wn.synset(‘mint.n.04‘).substance_holonyms() 22 [Synset(‘mint.n.05‘)]
2）蕴涵关系
1 >>> wn.synset(‘walk.v.01‘).entailments() 2 [Synset(‘step.v.01‘)] 3 >>> wn.synset(‘eat.v.01‘).entailments() 4 [Synset(‘chew.v.01‘), Synset(‘swallow.v.01‘)] 5 >>> wn.synset(‘tease.v.03‘).entailments() 6 [Synset(‘arouse.v.07‘), Synset(‘disappoint.v.01‘)]
3）反义词
1 >>> wn.lemma(‘supply.n.02.supply‘).antonyms() 2 [Lemma(‘demand.n.02.demand‘)] 3 >>> wn.lemma(‘rush.v.01.rush‘).antonyms() 4 [Lemma(‘linger.v.04.linger‘)] 5 >>> wn.lemma(‘horizontal.a.01.horizontal‘).antonyms() 6 [Lemma(‘inclined.a.02.inclined‘), Lemma(‘vertical.a.01.vertical‘)] 7 >>> wn.lemma(‘staccato.r.01.staccato‘).antonyms() 8 [Lemma(‘legato.r.01.legato‘)] 9 >>>
4. 语义相似度
同义词集是由复杂的词汇关系网络所连接起来的。给定一个同义词集，可以遍历WordNet网络来查找相关含义的同义词集。每个同义词集都有一个或多个上位词路径连接到一个根上位词。连接到同一个根的两个同义词集可能有一些共同的上位词。如果两个同义词集共用一个特定的上位词——在上位词层次结构中处于较底层——它们一定有密切的联系。
原文：http://www.cnblogs.com/no-tears-girl/p/6416765.html
