H-Huang/complex_word_identification huggingface dataset:
Other attractions include the Al Ain Oasis in the city center , other oases dotted around the area - all cool retreats in the middle of the summer heat - Al Ain Zoo , an amusement park named `` Hili Fun City '' , many well-maintained parks popular with families in the summer evenings , and a heritage village .
Target word: well-maintained — judged complex by 5 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.3)
Target word: park — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: named — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Hili — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Fun — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: City — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: heritage — judged complex by 8 of 10 native annotators and 7 of 10 non-native annotators (probability complex: 0.75)
Target word: parks — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: popular — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: families — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: summer — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: evenings — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: heritage village — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: village — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Al Ain ( Arabic : العين , al-ʿayn , literally The Spring ) , also known as the Garden City due to its greenery , is the second largest city in the Emirate of Abu Dhabi and the fourth largest city in the United Arab Emirates .
Target word: literally — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: Al — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Ain — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Arabic — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: al-ʿayn — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: greenery — judged complex by 8 of 10 native annotators and 8 of 10 non-native annotators (probability complex: 0.8)
Target word: Spring — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Garden — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: City — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: due — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Emirate — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: largest — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: city — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Abu Dhabi — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: Abu — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: United Arab Emirates — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: Dhabi — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: fourth — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: largest — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: city — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: United — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Emirates — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: Arab — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
In the time of William Shakespeare , women 's roles were generally played by men or boys .
Target word: roles — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: time — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: William — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Shakespeare — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: women — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: generally — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: played — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: men — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: boys — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
The stage role of Peter Pan , for example , is traditionally played by a woman , as are most principal boys in British pantomime .
Target word: stage — judged complex by 0 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.1)
Target word: traditionally — judged complex by 2 of 10 native annotators and 6 of 10 non-native annotators (probability complex: 0.4)
Target word: role — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Peter — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Pan — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: principal — judged complex by 7 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.45)
Target word: played — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: woman — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: principal boys — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: pantomime — judged complex by 10 of 10 native annotators and 10 of 10 non-native annotators (probability complex: 1.0)
Target word: boys — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: British — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Opera has several `` breeches roles '' traditionally sung by women , usually mezzo-sopranos .
Target word: Opera — judged complex by 1 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.15)
Target word: breeches — judged complex by 2 of 10 native annotators and 5 of 10 non-native annotators (probability complex: 0.35)
Target word: breeches roles — judged complex by 4 of 10 native annotators and 5 of 10 non-native annotators (probability complex: 0.45)
Target word: traditionally — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: roles — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: sung — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: mezzo-sopranos — judged complex by 10 of 10 native annotators and 8 of 10 non-native annotators (probability complex: 0.9)
Target word: women — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Examples are Hansel in Hänsel und Gretel , Cherubino in The Marriage of Figaro and Octavian in Der Rosenkavalier .
Target word: Hänsel — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Examples — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Hansel — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Gretel — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: und — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Cherubino — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: Figaro — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: Marriage — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Octavian — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: Der Rosenkavalier — judged complex by 2 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.1)
Target word: Der — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Rosenkavalier — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
In the former film Linda Hunt played the pivotal role of Billy Kwan , for which she received the Academy Award for Best Supporting Actress .
Target word: former — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: pivotal — judged complex by 7 of 10 native annotators and 8 of 10 non-native annotators (probability complex: 0.75)
Target word: film — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Linda — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Hunt — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: played — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: pivotal role — judged complex by 0 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.1)
Target word: Academy Award — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: role — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Billy — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Kwan — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: received — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Academy — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Supporting — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: Award — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Best — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Actress — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Having an actor dress as the opposite sex for comic effect is also a long-standing tradition in comic theater and film .
Target word: opposite — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: Having — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: actor — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: dress — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: opposite sex — judged complex by 2 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.1)
Target word: long-standing — judged complex by 2 of 10 native annotators and 4 of 10 non-native annotators (probability complex: 0.3)
Target word: sex — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: comic — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: effect — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: long-standing tradition — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: tradition — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: comic — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: comic theater — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: theater — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: film — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
The Russian military is divided into the following branches : the Russian Ground Forces , the Russian Navy , and the Russian Air Force .
Target word: military — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: Russian — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: divided — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: following — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: branches — judged complex by 3 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.2)
Target word: Russian — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Ground — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Forces — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Russian — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Navy — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Russian — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Air — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Force — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
As of 2008 ( update ) , some 480,000 young men are brought into the Army via Conscription in Russia in two call-ups each year .
Target word: update — judged complex by 0 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.1)
Target word: brought — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: young — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: men — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: via — judged complex by 2 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.1)
Target word: Army — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Conscription — judged complex by 10 of 10 native annotators and 10 of 10 non-native annotators (probability complex: 1.0)
Target word: call-ups — judged complex by 6 of 10 native annotators and 7 of 10 non-native annotators (probability complex: 0.65)
Target word: Russia — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: year — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
It has been founded in 1991 by the Austrian writer , artist and musician Paul Jaeg .
Target word: founded — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: Austrian — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: writer — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: artist — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: musician — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Paul — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Jaeg — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Some authors , such as Peter Paul Wiplinger , have already several books with Arovell , but others use the publishing house as a platform to publish their first book ( s ) .
Target word: Wiplinger — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: authors — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Peter — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Paul — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Arovell — judged complex by 3 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.15)
Target word: books — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: publishing — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: publishing house — judged complex by 1 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.1)
Target word: platform — judged complex by 2 of 10 native annotators and 6 of 10 non-native annotators (probability complex: 0.4)
Target word: house — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: publish — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: book — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
The covers of all books edited by Arovell show a painting respectively a section from a painting by Paul Jaeg .
Target word: covers — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: edited — judged complex by 0 of 10 native annotators and 2 of 10 non-native annotators (probability complex: 0.1)
Target word: books — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Arovell — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: respectively — judged complex by 8 of 10 native annotators and 4 of 10 non-native annotators (probability complex: 0.6)
Target word: show — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: painting — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: section — judged complex by 0 of 10 native annotators and 1 of 10 non-native annotators (probability complex: 0.05)
Target word: Jaeg — judged complex by 1 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.05)
Target word: painting — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)
Target word: Paul — judged complex by 0 of 10 native annotators and 0 of 10 non-native annotators (probability complex: 0.0)