def winner_text(factsys, data, win):
factsys.grammar.embed("G")
import G
name = G.pnameName(pname(win))
priz = factsys.str2exp("Prize", win.prize)
cit = cname(factsys, win.city)
countr = cname(factsys, win.country)
doc = G.OneSentenceDoc(
G.ContinuousPastFactSentence( ## for Ger
G.ActFact(G.NameObject(name),
G.winPrizeDateAct(priz, string_year(win.year)))))
doc = G.AddSentenceDoc(
doc,
G.ContinuousPastFactSentence(
G.ActFact(G.PronObject(name),
G.bornAct(string_year(win.born), cit, countr))))
if len(win) > 7 and win.dead:
try:
fname = G.pnameName(pname(win, just_family=True))
doc = G.AddSentenceDoc(
doc,
G.PunctualPastFactSentence(
G.ActFact(G.NameObject(fname),
G.dieAct(string_year(win.dead)))))
except:
pass
## print(doc)
return doc, name, priz
def country_texts_embedded(factsys, data):
factsys.grammar.embed("G")
import G
fields = factsys.fieldnames.split()
facts = []
for tuple in data:
countr = factsys.str2exp("Name", tuple[0])
cap = factsys.str2exp('Name', tuple.capital)
cont = factsys.str2exp('Name', tuple.continent).unpack()[1][0] #CDNAME
curr = factsys.str2exp('Name', tuple.currency)
pop = pgf.readExpr(str(tuple.population))
are = pgf.readExpr(str(tuple.area))
doc = G.OneSentenceDoc(
G.FactSentence(
G.KindFact(
G.NameObject(countr),
G.ModifierKind(
G.PropertyKind(G.cdProperty(cont), G.country_Kind),
G.NumericKindModifier(G.IntNumeric(pop),
G.inhabitant_Kind)))))
doc = G.AddSentenceDoc(
doc,
G.FactSentence(
G.AttributeFact(G.area_Attribute, G.PronObject(countr),
G.NumericValue(G.IntNumeric(are)))))
doc = G.AddSentenceDoc(
doc,
G.ConjSentence(
G.FactSentence(
G.AttributeFact(G.capital_Attribute, G.NameObject(countr),
G.NameValue(cap))),
G.FactSentence(
G.AttributeFact(G.currency_Attribute, G.PronObject(countr),
G.NameValue(curr)))))
facts.append(doc)
return facts
def continent_text(factsys, data, cont):
factsys.grammar.embed("G")
import G
facts = []
cont_data = [d for d in data if cont in [d.continent, the_world]]
ncountries = len(cont_data)
largestpop = max(cont_data, key=lambda c: int(c.population)).country
largestarea = max(cont_data, key=lambda c: int(c.area)).country
totalpop = sum([int(c.population) for c in cont_data]) // 1000000
doc = factsys.str2exp("Doc", ("there are {} countries in {}.").format(
ncountries, cont))
doc = G.AddSentenceDoc(
doc,
factsys.str2exp("Sentence",
("the total population of {} is {} million").format(
cont, totalpop)))
doc = G.AddSentenceDoc(
doc,
factsys.str2exp(
"Sentence",
("{} has the largest population and {} has the largest area"
).format(largestpop, largestarea)))
billions = [c.country for c in cont_data if int(c.population) > 1000000000]
if len(billions) == 1:
subject = billions[0]
property = ' is the only country '
elif len(billions) > 1:
subject = ', '.join(billions[:-1]) + ' and ' + billions[-1]
property = ' are the only countries '
if billions:
doc = G.AddSentenceDoc(
doc,
factsys.str2exp(
'Sentence',
subject + property + 'with over a billion inhabitants'))
return doc
def nobel_texts(factsys, data):
factsys.grammar.embed("G")
import G
def first_woman(p):
return min(filter(lambda w: w.sex == 'female' and w.prize == p, data),
key=lambda d: int(d.year[:4])).winner
def youngest(p):
return min(filter(lambda w: w.prize == p, data),
key=lambda d: int(d.year[:4]) - int(d.born[:4])).winner
docs = []
for win in data:
doc, name, priz = winner_text(factsys, data, win)
if win.winner == first_woman(win.prize):
doc = G.AddSentenceDoc(
doc,
G.ContinuousPastFactSentence(
G.FirstInKindFact(
G.NameObject(name),
G.ModifierKind(
G.woman_Kind,
G.PunctualPastActModifier(G.winPrizeAct(priz))))))
if win.winner == youngest(win.prize):
if win.sex == 'female':
winnerOf = G.femaleWinnerOfPrizeKind
else:
winnerOf = G.maleWinnerOfPrizeKind
doc = G.AddSentenceDoc(
doc,
G.ContinuousPastFactSentence(
G.YoungestInKindFact(G.PronObject(name), winnerOf(priz))))
docs.append(doc)
return docs
