def interpret(self, match):
#print(dir(match), match.director, match.words)
movie = IsMovie() + DirectedBy(match.director)
movie_name = NameOf(movie)
print(movie_name)
return movie_name, "enum"
def interpret(self, match):
movie = IsMovie() + HasActor(match.actor)
movie_name = NameOf(movie)
name_dir = ''.join(match.actor.nodes[0][1][1].split('"')[:-1])
names = name_dir.split()
if u"recent" in [k.lemma for k in match.words]:
movie_name.head = "a.name,a.surname,a.title"
if len(names) == 1:
movie_name.nodes = [
u' name like "' + names + '" and b.year>YEAR(curdate())-2'
]
else:
movie_name.nodes = [
u' name like "' + u" ".join(names[:-1]) +
u'" and surname like "' + names[-1] +
'" and b.year>YEAR(curdate())-2'
]
movie_name.head = u"a.title"
movie_name.tables = [
"actors as a left join movies as b on(a.movie_id=b.id) ",
"actresses as a left join movies as b on(a.movie_id=b.id) "
]
#print("definition ",definition)
else:
movie_name.tables = ["actors", "actresses"]
movie_name.head = "title,name,surname"
if len(names) == 1:
movie_name.nodes = [u' name like "' + names + '"']
else:
movie_name.nodes = [
u' name like "' + u" ".join(names[:-1]) +
u'" and surname like "' + names[-1] + '"'
]
return movie_name, ("enum", "ActedOnQuestion")
def interpret(self, match):
movie = IsMovie() + HasActor(match.actor)
movie_name = NameOf(movie)
print(movie_name.__dict__)
return movie_name, "enum"
def interpret(self, match):
name = match.words.tokens
return IsMovie() + HasName(name)
def interpret(self, match):
movie = IsMovie()
name = NameOf(movie)
return name, "enum"
def interpret(self, match):
_director, i, j = match.director
movie = IsMovie() + DirectedBy(_director)
movie_name = LabelOf(movie)
return movie_name, ReturnValue(i, j)
def interpret(self, match):
_actor, i, j = match.actor
movie = IsMovie() + HasActor(_actor)
movie_name = NameOf(movie)
return movie_name, ReturnValue(i, j)
def interpret(self, match):
movie = IsMovie() + DirectedBy(match.director)
movie_name = LabelOf(movie)
return movie_name, "enum"
def interpret(self, match):
name = match.words.tokens
exp = IsMovie()
exp.tables = ["movies"]
return IsMovie() + HasName(name)
def interpret(self, match):
print('match')
print(match.__dict__)
print('match._match')
print(match._match.__dict__)
print('match.target')
print(match.target.__dict__)
# match.target exists just because of the Group(Movie(), "target")
print('match.target.tokens')
print(match.target.tokens)
print('haskeyword')
print(HasKeyword(match.target.tokens).__dict__)
movie = IsMovie()
movie_name = NameOf(movie)
"""
{'nodes': [[(u'rdf:type', u'dbpedia-owl:Film'), ('foaf:name', 1)]], 'fixedtyperelation': u'rdf:type', 'head': 0, 'fixedtype': u'dbpedia-owl:Film'}
"""
print('movie (ismovie)')
print(movie.__dict__)
"""
{'nodes': [[(u'rdf:type', u'dbpedia-owl:Film'), ('foaf:name', 1)], []], 'head': 1}
"""
print('moviename (nameof(ismovie))')
print(movie_name.__dict__)
print('words are classes, not just simple texts')
first_word = match.words[
0] # {'lemma': u'list', 'token': u'list', 'pos': u'NN', 'prob': None}
second_word = match.words[
1] # {'lemma': u'movie', 'token': u'movies', 'pos': u'NNS', 'prob': None}
print('first word')
print(first_word.__dict__)
print('second word')
print(second_word.__dict__)
print(match.target.tokens)
matched_lemmas = [k.lemma for k in match.words]
recent = u"recent" in matched_lemmas
popular = u"popular" in matched_lemmas
select_expressions = ["title"]
if hasattr(match, 'genre'):
tables = [u"genres"]
condition_cols = [u"genre"]
condition_values = [
''.join(match.genre.nodes[0][1][1].split('"')[:-1])
]
else:
tables = [u"title"]
condition_cols = []
condition_values = []
generate_nodes_tables(movie_name,
tables,
select_expressions,
condition_cols=condition_cols,
condition_values=condition_values,
popular=popular,
recent=recent)
movie_name.nodes[0] += " limit 10" #[u'title like "'+match.movie+'"']
print "nodes", movie_name.nodes
print movie_name
return movie_name, ("enum", "ListMoviesQuestion")
def interpret(self, match):
movie = IsMovie() + HasActor(match.actor)
movie_name = LabelOf(movie)
return movie_name, "enum"