Logistic linguisticsBengt Sigurd & Mats Eeg-OlofssonFrom first sound/morpheme/word to last via shorter
combinable roads (dyads)Logistic syllable analysis: st-tr-ra-an-nd
Logistic kinship analysis:x,kusin,w :- x,barn,y,y,syskon,z,z,föräld,wLogistic morphology:o,be-be,slut-slut,sam
Logistic text generation bo-pengar: bo,känner,leif,flyger,helikopter,
landar,tak,har,värdedepå,har,pengar
Dyads in onset + coda in syllables
• [[s,t],[t,r],[r,a]]+[[a,n],[n,d]] % strand• [[t,r],[r,a]]+[[a,s],[s,t]] % trast• [[s,t],[t,a]]+[[a,r,[r,t]] % start• [[s,p],[p,r],[r,e]]+[[e,l][l,s]] % sprels
Syllable duration derived and measured
• Measured data predicted values • dur([p,e,l],538). 541 • dur([s,p,e,l],743). 741 • dur([p,e,l,s],805). 729 • dur([r,e,l],536). 527 • dur([p,r,e],552). 568 • dur([s,p,r,e,l],835). 832 • dur([s,p,r,e,l,s],1028). 1020
Släktträd/nätverk
Philip partner to Vera
• \ /• child to• / | \• Bill partner to Una Karin Thomas part to Gerd • \ / \ /
child to child to/ \ / \
• John Maria Charles Anne
Släktträd/nätverk
English demos erel(A,B,C,D)How are A and B related?
• No.1 : A = 'John', B = 'Charles’,C = 3, D = ['John', cousin, to, 'Charles’]
• No.20 : A = 'John', B = 'Maria', C = 1, D = ['John', sibling, to, 'Maria']
• No.44 : A = 'Una', B = 'Karin', C = 1, D = ['Una', sister, to, 'Karin']
• No.102 : A = 'John', B = 'Karin', C = 2, D = ['John', nephew, to, 'Karin']
• No.109 : A = 'Maria', B = 'Thomas', C = 2, D = ['Maria', niece, to, 'Thomas']
word(A, B, C, D) generating more or less comprehensible words
No.1 : A = o, B = trött, C = 2, D = [o, trött]No.1 : A = o, B = sam, C = 3, D = [o, akt, sam]No.2 : A = för, B = sam, C = 3, D = [för, trött, sam]No.3 : A = o, B = lig, C = 4, D = [o, för, son, lig]No.4 : A = o, B = sam, C = 4, D = [o, för, akt, sam]No.5 : A = o, B = het, C=5, D = [o, för, son, lig,het]No.6 : A = o, B = het, C = 6, D = [o, för, be, akt,sam, het]
rel(A,B, C, D) % looking for relations sten-maria,bertil-pengar
• rel(sten,maria,C,D)• No.1 : C = 5, D = [sten, gör, ibland, smuggling, vanligt, i, hamn, finns, i,
malmö, hemstad, för, per, känner, nog, maria]• rel(bertil, pengar, C, D), C>8• No.1 : C = 12, D = [bertil, förälder, till, jarl, bodde, i, malmö, hemstad,
för, per, känner, nog, maria, arbetade, på, bonniers, hyste, tidvis, jacob, gick, på, sigtuna, hyste, tidvis, leif, flyger, ibland, helikopter, landar, på, tak, finns, på, depå, ger, ofta, pengar]
•
Dyads of grammatical categories in onset + coda in Logistic grammar
• [[hunden,bet]]+[[bet,inte],[inte,råttan],[råttan,.]]• [[N,Vt]]+[[Vt,Ne],[Ne,N],[N,’.’]]
• Subordinate clause• (att) [[hunden,inte],[inte,bet]]+[bet,råttan],
[råttan,’,’]]• [[N,Ne],[Ne,Vt]]+[Vt,N],[N,’,’]]
Prolog for sents as onset + coda
• sents(X,Z,C3,D3) :- oo(X,Y,C,D), • cc(Y,Z,C2,D2),D2=[H|T],append(D,T,D3),• C3 is C + C2. % sats består av onset(D) samt
coda(D2) som har verb som brygga• Onset rules (dyads)• o(N,V,1,[N,V]) :- np(N),v(V).• o(N,V,1,[N,V]) :- np(N),vt(V).• o(N,V,1,[N,V]) :- np(N),aux(V).
Sent codas• c(V,'.',1,[V,'.']) :- v(V). % final v med punkt• c(V,N,1,[V,N]) :- vt(V),np(N). % bet hund• c(N,'.',1,[N,'.']) :- np(N). % final obj n med .• c(N,A,1,[N,A]) :- np(N),adv(A). % obj n +A • c(A,'.',1,[A,'.']) :- adv(A). % final adv med .• c(V,Ne,1,[V,Ne]) :- vt(V),neg(Ne). % bet inte • c(Ne,A,1,[Ne,A]) :- neg(Ne),adv(A). % inte A• c(Ne,N,1,[Ne,N]) :- neg(Ne),np(N). % inte hund• c(X,Y,1,[X,Y]) :- aux(X),inf(Y). % kan komma
Lexicon• n(hunden).• n(katten).• n(gatan).• rel(som).• v(föll).• v(kom).• vt(bet).• adv(snabbt).
Lexicon
• c(när).• p(på).• aux(kan).• inf(komma).• neg(inte).• np(N) :- n(N).• adv([P,N]) :- p(P),np(N).
Demos main sents• sents(A, ., C, D) % final punkt required• No.1 : A = hunden, C = 2, D = [hunden, föll, .]• No.2 : A = katten, C = 3, D = [katten, bet, hunden, .]• No.3 : A = katten, C = 4, D = [katten, bet, hunden,
snabbt, .]• No.7 : A = katten, C = 4, D = [katten, bet, hunden,
[på, gatan], .]• No.14 : A = hunden, C = 4, D = [hunden, bet, inte,
snabbt, .]
Np med rel, Adv clauses
np(Np) :- n(N),sentr(A,B,C,D),append([N],D,Np).% N with subj relative clausenp(Np) :- n(N),sentro(A,B,C,D),append([N],D,Np). % N with obj relative clause
adv(D2) :- c(Cu),sentu(A,B,C,D),append([Cu],D,D2).% conjunc with sub clause
Inverted word order
• oi(A,B,1,[A,B]) :- adv(A),v(B). % snabbt föll • oi(A,B,1,[A,B]) :- adv(A),vt(B). % snabbt bet • ci(N,'.',1,[N,'.']) :- n(N). % (snabbt föll) n med . • ci(V,N2,1,[V,N,N2]) :- vt(V),n(N),n(N2). % (snabbt)
bet katt hund• ci(V,N2,1,[V,N,Ne,N2]) :- vt(V),n(N),neg(Ne),n(N2).
% (snabbt) bet katt inte hund• ci(N,A,1,[N,A]) :- n(N),adv(A). % (bet) hund snabbt
Demos inverted• senti(A, ., C, D)• No.1 : A = snabbt, C = 3, D = [snabbt, föll,
hunden, .]• No.6 : A = snabbt, C = 4, D = [snabbt, föll,
hunden, [på, gatan], .]• No.13 : A = [på, gatan], C = 3, D = [[på, gatan],
föll, hunden, .]• No.30 : A = snabbt, C = 4, D = [snabbt, bet,
katten, hunden, [på, gatan], .]• No.31 : A = snabbt, C = 3, D = [snabbt, bet,
katten, inte, hunden, .]
Demo with rel and adv clausesents(A, B, C, [hunden, som, kom, föll, .])• No.1 : A = hunden, B = ., C = 5• sents(A, B, C, [katten, som, föll, bet, inte, hunden,
snabbt, .])• No.1 : A = katten, B = ., C = 8• sents(A, B, C, [hunden, som, katten, bet,
[när,hunden,föll], föll, .])• No.1 : A = hunden, B = ., C = 5• sents(A, B, C, [hunden, som, katten, bet, bet, katten,
.])• No.1 : A = hunden, B = ., C = 6
Conclusions• It is possible to describe (generate) all(?)
types of sentences by logistic grammarCan one scale-up the test grammar adding e.g.
coordination and using available lexicons? Does logistic grammar offer new interesting typological
possibilities?Does logistic grammar offer new pedagogical possibilities?Can one predict the processing and duration of sentences
by logistic linguistics?How does logistic grammar relate to other types of
grammar?