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| /* | ||
| Stochastic logic program defining a distribution over simple sentences with number agreement. The sentences are defined using a definite clause grammars. | ||
| Recall that in SLPs, the probabilities of all rules with the same head predicate sum to one and define a mutually exclusive choice on how to continue a proof. | ||
| Furthermore, repeated choices are independent, i.e., no stochastic memoization | ||
| Form https://dtai.cs.kuleuven.be/problog/tutorial/various/06_slp.html#stochastic-logic-programs | ||
| */ | ||
| :- use_module(library(mcintyre)). | ||
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| :- if(current_predicate(use_rendering/1)). | ||
| :- use_rendering(c3). | ||
| :- endif. | ||
| :- mc. | ||
| :- begin_lpad. | ||
| % a stochastic logic program defining a distribution over simple sentences with number agreement | ||
| % recall that in SLPs, the probabilities of all rules with the same head predicate sum to one and define a mutually exclusive choice on how to continue a proof | ||
| % furthermore, repeated choices are independent, i.e., no stochastic memoization | ||
| % | ||
| % 1.0 : s(List) :- | ||
| % s(List,[]). | ||
| % | ||
| % 1.0 : s(List,Rest) :- | ||
| % np(List,Mid,Number), | ||
| % vp(Mid,Rest,Number). | ||
| % | ||
| % 0.4 : np(List,Rest,sing) :- | ||
| % det(List,Mid,sing), | ||
| % n(Mid,Rest,sing). | ||
| % 0.4 : np(List,Rest,pl) :- | ||
| % n(List,Rest,pl). | ||
| % 0.2 : np(List,Rest,pl) :- | ||
| % det(List,Mid,pl), | ||
| % n(Mid,Rest,pl). | ||
| % | ||
| % 1.0 : vp(List,Rest,Num) :- | ||
| % v(List,Mid,Num), | ||
| % np(Mid,Rest,_). | ||
| % | ||
| % 1/3 : det([the|L],L,pl). | ||
| % 1/3 : det([the|L],L,sing). | ||
| % 1/3 : det([a|L],L,sing). | ||
| % | ||
| % 0.25 : n([cat|L],L,sing). | ||
| % 0.15 : n([mouse|L],L,sing). | ||
| % 0.1 : n([dog|L],L,sing). | ||
| % 0.25 : n([cats|L],L,pl). | ||
| % 0.15 : n([mice|L],L,pl). | ||
| % 0.1 : n([dogs|L],L,pl). | ||
| % | ||
| % 0.35 : v([chases|L],L,sing). | ||
| % 0.15 : v([sees|L],L,sing). | ||
| % 0.2 : v([chase|L],L,pl). | ||
| % 0.3 : v([see|L],L,pl). | ||
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| % use counter-based trial IDs for each head predicate with a stochastic choice, and explicit split rather than difference lists | ||
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| % s(Num) -> np(Num),vp(Num) | ||
| s(W,Num,np(N,NN),det(D,DD),n(M,MM),v(V,VV)) :- | ||
| split(W,W1,W2), | ||
| np(W1,Num,np(N,NI),det(D,DI),n(M,MI),v(V,VI)), | ||
| vp(W2,Num,np(NI,NN),det(DI,DD),n(MI,MM),v(VI,VV)). | ||
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| % np(Num) -> 0.4:: det(sg),n(sg) | 0.4:: n(pl) | 0.2::det(pl),n(pl) | ||
| np_to(N,sg_dn):0.4; np_to(N,pl_n):0.4; np_to(N,pl_dn):0.2. | ||
| np(W,sg,np(N,NN),det(D,DD),n(M,MM),v(V,VV)) :- | ||
| np_to(N,sg_dn), | ||
| NI is N+1, | ||
| split(W,W1,W2), | ||
| det(W1,sg,np(NI,N1),det(D,D1),n(M,M1),v(V,V1)), | ||
| n(W2,sg,np(N1,NN),det(D1,DD),n(M1,MM),v(V1,VV)). | ||
| np(W,pl,np(N,NN),det(D,DD),n(M,MM),v(V,VV)) :- | ||
| np_to(N,pl_n), | ||
| NI is N+1, | ||
| n(W,pl,np(NI,NN),det(D,DD),n(M,MM),v(V,VV)). | ||
| np(W,pl,np(N,NN),det(D,DD),n(M,MM),v(V,VV)) :- | ||
| np_to(N,pl_dn), | ||
| NI is N+1, | ||
| split(W,W1,W2), | ||
| det(W1,pl,np(NI,N1),det(D,D1),n(M,M1),v(V,V1)), | ||
| n(W2,pl,np(N1,NN),det(D1,DD),n(M1,MM),v(V1,VV)). | ||
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| % vp(Num) -> v(Num), np(_) | ||
| vp(W,Num,np(N,NN),det(D,DD),n(M,MM),v(V,VV)) :- | ||
| split(W,W1,W2), | ||
| v(W1,Num,np(N,NI),det(D,DI),n(M,MI),v(V,VI)), | ||
| np(W2,_,np(NI,NN),det(DI,DD),n(MI,MM),v(VI,VV)). | ||
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| % det(Num) -> 1/3 the(pl) | 1/3 the(sg) | 1/3 a(sg) | ||
| det_to(N,the_pl):1/3; det_to(N,the_sg):1/3; det_to(N,a_sg):1/3. | ||
| det([the],pl,np(N,N),det(D,DD),n(M,M),v(V,V)) :- | ||
| det_to(D,the_pl), DD is D+1. | ||
| det([the],sg,np(N,N),det(D,DD),n(M,M),v(V,V)) :- | ||
| det_to(D,the_sg), DD is D+1. | ||
| det([a],sg,np(N,N),det(D,DD),n(M,M),v(V,V)) :- | ||
| det_to(D,a_sg), DD is D+1. | ||
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| % n(Num) -> 0.25 cat(sg) | 0.15 mouse(sg) | 0.1 dog(sg) | 0.25 cats(pl) | 0.15 mice(pl) | 0.1 dogs(pl) | ||
| n_to(N,cat_sg):0.25; n_to(N, mouse_sg):0.15 ; n_to(N, dog_sg):0.1 ; n_to(N, cats_pl):0.25 ; n_to(N, mice_pl):0.15 ; n_to(N, dogs_pl):0.1. | ||
| %n_to(N,cat_sg):0.5; n_to(N, mouse_sg):0.3 ; n_to(N, dog_sg):0.2. | ||
| % n_to(N, cats_pl):0.5 ; n_to(N, mice_pl):0.3 ; n_to(N, dogs_pl):0.2. | ||
| n([cat],sg,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,cat_sg), MM is M+1. | ||
| n([mouse],sg,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,mouse_sg), MM is M+1. | ||
| n([dog],sg,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,dog_sg), MM is M+1. | ||
| n([cats],pl,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,cats_pl), MM is M+1. | ||
| n([mice],pl,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,mice_pl), MM is M+1. | ||
| n([dogs],pl,np(N,N),det(D,D),n(M,MM),v(V,V)) :- | ||
| n_to(M,dogs_pl), MM is M+1. | ||
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| % v(Num) -> 0.35 chases(sg) | 0.15 sees(sg) | 0.2 chase(pl) | 0.3 see(pl) | ||
| v_to(N, chases_sg):0.35 ; v_to(N, sees_sg):0.15 ; v_to(N, chase_pl):0.2 ; v_to(N, see_pl):0.3. | ||
| v([chases],sg,np(N,N),det(D,D),n(M,M),v(V,VV)) :- | ||
| v_to(V,chases_sg), VV is V+1. | ||
| v([sees],sg,np(N,N),det(D,D),n(M,M),v(V,VV)) :- | ||
| v_to(V,sees_sg), VV is V+1. | ||
| v([chase],pl,np(N,N),det(D,D),n(M,M),v(V,VV)) :- | ||
| v_to(V,chase_pl), VV is V+1. | ||
| v([see],pl,np(N,N),det(D,D),n(M,M),v(V,VV)) :- | ||
| v_to(V,see_pl), VV is V+1. | ||
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| % initialize all counters to 0, and leave number open | ||
| word(L) :- s(L,_Num,np(0,_),det(0,_),n(0,_),v(0,_)). | ||
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| % split(+T,-P,-S) splits the list T into two non-empty sublists P(refix) and S(uffix) | ||
| % note that T needs to have fixed length for this to terminate | ||
| split([A,B|C],[A],[B|C]). | ||
| split([A,B|C],[A|D],E) :- | ||
| split([B|C],D,E). | ||
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| % compute posteriors of correct sentences (or sample a correct sentence) | ||
| % we need to fix the length of the list to ensure split/3 has a finite number of solutions | ||
| query(X):-X=[_,_,_,_,_],word(X). | ||
| query(X):-X=[_,_,_,_],word(X). | ||
| query(X):-X=[_,_,_],word(X). | ||
| evidence(is_word). | ||
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| % this grammar can only produce words of length 3/4/5 | ||
| % the probability of getting a word is 0.067222 | ||
| is_word :- word([_,_,_]). | ||
| is_word :- word([_,_,_,_]). | ||
| is_word :- word([_,_,_,_,_]). | ||
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| :- end_lpad. | ||
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| /** <examples> | ||
| ?- mc_mh_sample_arg(word([A,B,C]),word([_,_,_]),10,1,[A,B,C],V). | ||
| % take 10 samples of 3 token words given that the lenght of the word is 3 | ||
| ?- mc_mh_sample_arg_bar(word([A,B,C]),word([_,_,_]),10,1,[A,B,C],V). | ||
| % take 10 samples of 3 token words given that the lenght of the word is 3 | ||
| % and draw a bar chart of the results | ||
| ?- mc_mh_sample_arg(query(X),is_word,10,1,X,V). | ||
| % take 10 samples of 3, 4 or 5 token words given that the lenght of the word is | ||
| % 3, 5 or 5 | ||
| % | ||
| */ | ||
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