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我的拉丁翻譯器出現問題，我正在爲一個學校項目建立。我爲拉丁/英語句子創建了一個語法。我創建了一個謂詞（可能的句子（拉丁語，英語）），它可以按照正確順序翻譯拉丁語句子。然而，由於拉丁語句子的排列順序不同，所以我採用了一系列排列組合來找到拉丁文翻譯成英語的正確順序。這是我的翻譯（拉丁語，英語）謂語。這看起來效率很低。有沒有更好的方法來做到這一點？非常低效且不雅的代碼
我也有加載一個大集從.csv謂詞看起來像這樣的其他文件：
noun("femin","femin",1,f,"woman","women").
verb("port","porta","portav","portat", 1, carry, carrying, carried).
這裏是我的主要程序：
% Nick's Latin translator
% --------------
% word generator
% --------------
% predicate used to see if any two of the stems join to the ending.
stem_ending_joiner(Stem1,Stem2,Ending,Latin) :-
(
append(Stem1,Ending,Latin),
!
; append(Stem2,Ending,Latin),
!
).
% predicate containing all possible data about nouns including endings
% and such
word_nounx(Latin,Translation,Gender,Case,Number) :-
noun(Stem1,Stem2,_,Gender,Sgtrans,Pltrans),
nounending(Ending,Prefix,Number,Case),
stem_ending_joiner(Stem1,Stem2,Ending,Latin),
(
Number = sg,
Translationw = Sgtrans;
Number = pl,
Translationw = Pltrans
),
append(Prefix," ",Prefixspace),
append(Prefixspace,Translationw,Translation).
% predicate containing all possible data about verbs including endings
% and such
% arguments: Latin,Translation,Tense,Number,Mood,Voice
word_verbx(Latin,Translation,Tense,Number,Mood,Voice,Person) :-
verb(Stem1,_,_,_,_,Ptrans,_,Pastrans),
verbending(Ending,Tense,Prefix,Number,Mood,Voice,Person),
stem_ending_joiner(Stem1,_,Ending,Latin),
(
Tense = present,
Translationw = Ptrans;
Tense = past,
Translationw = Pastrans
),
append(Prefix," ",Prefixspace),
append(Prefixspace,Translationw,Translation).
% -------
% parsing
% -------
word_noun(Latin,Translation,Gender,Case,Number) :-
word_nounx(Latinx,Translationx,Gender,Case,Number),
name(Latin,Latinx),
name(Translation,Translationx).
word_verb(Latin,Translation,Tense,Number,Mood,Voice,Person) :-
word_verbx(Latinx,Translationx,Tense,Number,Mood,Voice,Person),
name(Latin,Latinx),
name(Translation, Translationx).
pnoun(Gender,Case,Number) -->
[[English,Latin]],
{word_noun(Latin,English,Gender,Case,Number)}.
nounphrase(Gender,Case,Number) -->
pnoun(Gender,Case,Number).
pverb(Tense,Number,Mood,Voice,Person) -->
[[English,Latin]],
{word_verb(Latin,English,Tense,Number,Mood,Voice,Person)}.
verbphrase(Tense,Number,Mood,Voice,Person,Gender,Case,Nnumber) -->
pverb(Tense,Number,Mood,Voice,Person),
nounphrase(Gender,Case,Nnumber).
sentence -->
nounphrase(_,nom,Number),
verbphrase(_,Number,_,_,3,_,nom,_).
% Predicates which manipulate lists of list-pairs to get the first and
% last elements of each list.
headofelements([],[]).
headofelements([H|T],[[H|_]|T1]) :-
headofelements(T,T1).
tailofelements([],[]).
tailofelements([H|T],[[_|H]|T1]) :-
tailofelements(T,T1).
lastofelements([],[]).
lastofelements([H|T],[X|T1]) :-
last(X,N),
H = N,
lastofelements(T,T1).
% generates possible sentences with the latin and the english.
possible_sentence(X,N) :-
phrase(sentence,Y),
lastofelements(X,Y),
headofelements(N,Y).
translate(Latin,English) :-
permutation(Latin,X),
possible_sentence(X,English).
這裏是結局：
% --------------------------
% ADJECTIVE ENDINGS
% ------------------------------
adjending("us",sg,nom,m).
% -----------------------------------
% VERBENDINGS
% ------------------------------------
verbending("o",present,"I",sg,_,_,1).
verbending("as",present,"you",sg,_,_,2).
verbending("at",present,"He",sg,_,_,3).
verbending("amus",present,"We",pl,_,_,1).
verbending("atis",present,"You",pl,_,_,2).
verbending("ant",present,"They",pl,_,_,3).
% -----------------------------------
% NOUN ENDINGS
% -----------------------------------
nounending("a","",sg,nom).
nounending("am","",sg,acc).
nounending("ae","of",sg,gen).
nounending("ae","to",sg,dat).
nounending("a","with",sg,abl).
nounending("ae","",pl,nom).
nounending("as","",pl,acc).
nounending("arum","of",pl,gen).
nounending("is","to",pl,dat).
nounending("is","with",pl,abl).