| { |
| "paper_id": "E89-1013", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T10:34:13.383515Z" |
| }, |
| "title": "JPSG Parser on Constraint Logic Programming", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Tuda", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Hirosi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Hasida", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "hasida@icot.jp@relay.cs.net" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Kbiti", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hidetosi", |
| "middle": [], |
| "last": "Sirai", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
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| "abstract": "This paper presents a constraint logic programming language cu-Prolog and introduces a simple Japanese parser based on Japanese Phrase Structure Grammar (JPSG) as a suitable application of cu-Prolog. cu-Prolog adopts constraint unification instead of the normal Prolog unification. In cu-Prolog, constraints in terms of user defined predicates can be directly added to the program clauses. Such a clause is called Constraint Added Horn Clause (CAHC}. Unlike conventional CLP systems, cu-Prolog deals with constraints about symbolic or combinatorial objects. For natural language processing, such constraints are more important than those on numerical or boolean objects. In comparison with normal Prolog, cu-Prolog has more descriptive power, and is more declarative. It enables a natural implementation of JPSG and other unification based grammar formalisms.", |
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| "paper_id": "E89-1013", |
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| "abstract": [ |
| { |
| "text": "This paper presents a constraint logic programming language cu-Prolog and introduces a simple Japanese parser based on Japanese Phrase Structure Grammar (JPSG) as a suitable application of cu-Prolog. cu-Prolog adopts constraint unification instead of the normal Prolog unification. In cu-Prolog, constraints in terms of user defined predicates can be directly added to the program clauses. Such a clause is called Constraint Added Horn Clause (CAHC}. Unlike conventional CLP systems, cu-Prolog deals with constraints about symbolic or combinatorial objects. For natural language processing, such constraints are more important than those on numerical or boolean objects. In comparison with normal Prolog, cu-Prolog has more descriptive power, and is more declarative. It enables a natural implementation of JPSG and other unification based grammar formalisms.", |
| "cite_spans": [], |
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| "eq_spans": [], |
| "section": "Abstract", |
| "sec_num": null |
| } |
| ], |
| "body_text": [ |
| { |
| "text": "Prolog is frequently used in implementing natural language parsers or generators based on unification based grammars. This is because Prolog is also based on unification, and therefore has a declarative feature. One important characteristic of unification based grammar is also a declarative grammar formalization [11] .", |
| "cite_spans": [ |
| { |
| "start": 314, |
| "end": 318, |
| "text": "[11]", |
| "ref_id": "BIBREF13" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": "1" |
| }, |
| { |
| "text": "However, Prolog does not have sufficient power of expressing constraints because it executes every parts of its programs as procedures and because every variable of Prolog can be instantiated with any objects. Hence, the constraints in unification based grammar are forced to be implemented not declaratively but procedurally.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": "1" |
| }, |
| { |
| "text": "We developed a new constraint logic programming language cu-Prolog which is free from this defect of traditional Prolog [13] . In cu-Prolog, user defined constraints can be directly added to a program clause (constraint added Horn clause), and the constraint unification [12, 8] 1 is adopted instead of the nor-mal unification. This paper discusses the outline of the cu-Prolog system, and presents a Japanese parser based on :IPSG (Japanese Phrase Structure Grammar) [7] as a suitable application of cu-Prolog.", |
| "cite_spans": [ |
| { |
| "start": 120, |
| "end": 124, |
| "text": "[13]", |
| "ref_id": "BIBREF15" |
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| { |
| "start": 271, |
| "end": 275, |
| "text": "[12,", |
| "ref_id": "BIBREF14" |
| }, |
| { |
| "start": 276, |
| "end": 278, |
| "text": "8]", |
| "ref_id": "BIBREF10" |
| }, |
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| "text": "[7]", |
| "ref_id": "BIBREF9" |
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| ], |
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| "section": "Introduction", |
| "sec_num": "1" |
| }, |
| { |
| "text": "Most of the constraint logic programming language systems (CAL [2] , PrologIII [5] , etc.) deal with constraints about algebraic equations, i.e., constraints about numerical domains, such as that of real numbers etc. However, in the problems arising in Artificial Intelligence, constraints on symbolic or combinatorial objects are far more important than those on numerical objects, cu-Prolog handles constraints described in terms of sequence of atomic formulas of Prolog. The program clauses of cu-Prolog are following type, which we call Constraint Added Horn Clauses (CAHCs):", |
| "cite_spans": [ |
| { |
| "start": 63, |
| "end": 66, |
| "text": "[2]", |
| "ref_id": "BIBREF1" |
| }, |
| { |
| "start": 79, |
| "end": 82, |
| "text": "[5]", |
| "ref_id": "BIBREF6" |
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| ], |
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| "eq_spans": [], |
| "section": "Clause (CAHC)", |
| "sec_num": null |
| }, |
| { |
| "text": "1. H :-Bt,B2,...,Bn;C1,C2,...,Cm.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Clause (CAHC)", |
| "sec_num": null |
| }, |
| { |
| "text": "(H is called the head, B1, B2,... ,Bn is the body, C1, C2,..., Cm is the constraint. The body and the constraint can be empty.) C1,C2,...,Cm comprise a set of constraints on the variables occurring in the rest of the clause. C1, C2,..., Crn must be, in the current implementation, modular in the sense that it has the following canonical form.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Clause (CAHC)", |
| "sec_num": null |
| }, |
| { |
| "text": "[Def.] 1 (modular) A sequence of atomic formulas C1, C2,..., Cm is modular when is not undefined.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Clause (CAHC)", |
| "sec_num": null |
| }, |
| { |
| "text": "This transformation is done by repeating unfold/fold transformations as described later.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Clause (CAHC)", |
| "sec_num": null |
| }, |
| { |
| "text": "In normal Prolog, constraints are inserted in a goal and processed as procedures. It is not desirable for a declarative programming language, and the execution can be ineffective when constraints are inserted in a insufficient place.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Comparison with conventional approaches", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "As constraints are rewritten at every unification, cu-Prolog has more powerful descriptive ability than the bind-hook technique. For example, freeze in Prolog II [4] can impose constraints on one variable, so that when the variable is instantiated, the constraints are executed as a procedure. Freeze has, however, two disadvantages. First, freeze cannot impose a constraint on plural variables at one time. For example, it cannot express the following CAHC.", |
| "cite_spans": [ |
| { |
| "start": 162, |
| "end": 165, |
| "text": "[4]", |
| "ref_id": "BIBREF2" |
| } |
| ], |
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| "eq_spans": [], |
| "section": "Comparison with conventional approaches", |
| "sec_num": "3.2" |
| }, |
| { |
| "text": "Second, since the contradiction between constraints is not detected until the variable is instantiated, there is a possibility of executing useless computation in constraints deadlocking. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "f(X), g(Y, Z); append(X, Y, Z).", |
| "sec_num": null |
| }, |
| { |
| "text": "This subsection explains the mechanism of constraint transformation in cu-Prolog. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Constraint Transformation", |
| "sec_num": "3.3" |
| }, |
| { |
| "text": "Let C(A : -K&L.) be a clause in Pi, and D(B : -K'.) be a clause in :D, and 0 be mgu(K, K') that meets the following conditions. Then, 7~i+t is obtained by replacing C in :Pi with AO :-BO&L.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "fold transformation", |
| "sec_num": "2." |
| }, |
| { |
| "text": ". and adding E. E is also added to :D.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "fold transformation", |
| "sec_num": "2." |
| }, |
| { |
| "text": "The third transformation can be seen as a special case of fold transformation. Hence, these three transformations preserve the semantics of programs because unfold/fold transformation has been proved as valid [6] . ' The following example shows a transformation of member(A, Z), append(X, Y, Z). ", |
| "cite_spans": [ |
| { |
| "start": 209, |
| "end": 212, |
| "text": "[6]", |
| "ref_id": "BIBREF7" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "fold transformation", |
| "sec_num": "2." |
| }, |
| { |
| "text": "These clauses comprise the modular definition of p2.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T8 = p2([BIX] ,Y,A,Z) :-append(X,Y,Z).", |
| "sec_num": null |
| }, |
| { |
| "text": "Thus \"P3 = {T1, T2, T3, T4, T5', T6', TT, T8, D3}.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T8 = p2([BIX] ,Y,A,Z) :-append(X,Y,Z).", |
| "sec_num": null |
| }, |
| { |
| "text": "Unfold the second definition of D3, and we have", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "T8 = p2([BIX] ,Y,A,Z) :-append(X,Y,Z).", |
| "sec_num": null |
| }, |
| { |
| "text": "Folding TIO by D1 will generate TIO' = p3(A,Z,EBIX3,Y,B):-pI(A,X,Y,Z).", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "~9 4 = {T1, T2, T3, T4, T5 I, T6', TT, T8, Tg, TIO}.", |
| "sec_num": null |
| }, |
| { |
| "text": "\"P5 = {T1, T2, T3, T4, TS', T6', T7, T8, T9, TIO'}.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Accordingly", |
| "sec_num": null |
| }, |
| { |
| "text": "As a result,", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Accordingly", |
| "sec_num": null |
| }, |
| { |
| "text": "has been transformed to pl(A,X,Y,Z) preserving equivalefice, and the following new clauses have been defined.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "member(A, Z), append(X, Y, Z)", |
| "sec_num": null |
| }, |
| { |
| "text": "{T4, T5 I, T6 I, T7, T8, T9, TlOI}.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "member(A, Z), append(X, Y, Z)", |
| "sec_num": null |
| }, |
| { |
| "text": "The source code of cu-Prolog is, at present (Vet 2.0), composed of 4,500 lines of language C on UNIX system. Its precise computation speed is under evaluation, but is sufficient for practical use. Implementation of the effective constraint transformation shown in above subsection requires some heuristics in the application of three transformation. Especially, in unfold transformation, one atomic formula A is selected in the following heuristic rules 1. The atomic formula of the finite predicate.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Implementation", |
| "sec_num": "3.4" |
| }, |
| { |
| "text": "its arguments.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The atomic formula that has constants or [ ] in", |
| "sec_num": "2." |
| }, |
| { |
| "text": "3. The atomic formula that has lists in its argument. 4 . The atomic formula that has plural dependencies.", |
| "cite_spans": [ |
| { |
| "start": 54, |
| "end": 55, |
| "text": "4", |
| "ref_id": "BIBREF2" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The atomic formula that has constants or [ ] in", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Here ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The atomic formula that has constants or [ ] in", |
| "sec_num": "2." |
| }, |
| { |
| "text": "As an application of cu-Prolog, a natural language parser based on unification based grammar has been considered first of all. Since constraints can be added directly to the program clause representing a lexical entry or a phrase structure rule, the grammar is implemented more naturally and declaratively than with ordinary Prolog. Here we describe a simple Japanese parser of JPSG in cu-Prolog. CAHC plays an important role in two respects. First, CAHC is used in the lexicon of homonyms or polysemic words. For example, a Japanese noun \"hasi\" is 3-way ambiguous, it means a bridge, chopsticks, or an edge. This polysemic word can be subsumed in the following single lexical entry.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "A JPSG parser", |
| "sec_num": "4" |
| }, |
| { |
| "text": "where hasi_sem is defined as follows.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "lezieon([hasilX], X, [... semS EM]); hasi_sem( S E M ).", |
| "sec_num": null |
| }, |
| { |
| "text": "The value of the semantic feature is a variable (SEM), and the constraint on SEM is hasi_sem(SEM). Note that predicate hasi_sem is modularly defined. According to CAHC, such ambiguity may be considered at one time, instead of being divided in separate lexical entries. Japanese has such an ambiguity is also shown in conjugation, post positions, etc. They can be treated in this manner.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "hasi.sem( bridge ). hasi.sem( ehopst icks ). hasi.sem(edge).", |
| "sec_num": null |
| }, |
| { |
| "text": "Second, a phrase structure rule is written naturally in a CAHC. In JPSG [7] , FFP(FOOT Feature Principle) is:", |
| "cite_spans": [ |
| { |
| "start": 72, |
| "end": 75, |
| "text": "[7]", |
| "ref_id": "BIBREF9" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "hasi.sem( bridge ). hasi.sem( ehopst icks ). hasi.sem(edge).", |
| "sec_num": null |
| }, |
| { |
| "text": "The value of a FOOT feature of the mother unifies with the union of those of her daughters.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "hasi.sem( bridge ). hasi.sem( ehopst icks ). hasi.sem(edge).", |
| "sec_num": null |
| }, |
| { |
| "text": "This principle is embedded in a phrase structure rule as follows:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "hasi.sem( bridge ). hasi.sem( ehopst icks ). hasi.sem(edge).", |
| "sec_num": null |
| }, |
| { |
| "text": "However, this cannot be described in this manner in traditional Prolog. Figure 2 shows a simple demonstration of our JPSG parser, and Figure 3 shows an example of treating ambiguity as constraint. The current parser treats a few feature and has little lexicon. However, the expansion is easy. It parses about ten to twenty words sentences within a second on VAX8600. Since JPSG is a declarative grammar formalism and cu-Prolog describes JPSG also declaratively, the parser needs parsing algorithms independently. In the current implementation, we adopt the left corner parsing algorithm [1]. Furthermore, we would even be able to abandon parsing algorithm altogether [10] . The first line is a user's input. \"Ken-ga Naomi-wo ai-suru\" means \"Ken loves Naomi.\"", |
| "cite_spans": [ |
| { |
| "start": 667, |
| "end": 671, |
| "text": "[10]", |
| "ref_id": "BIBREF12" |
| } |
| ], |
| "ref_spans": [ |
| { |
| "start": 72, |
| "end": 80, |
| "text": "Figure 2", |
| "ref_id": "FIGREF9" |
| }, |
| { |
| "start": 134, |
| "end": 142, |
| "text": "Figure 3", |
| "ref_id": "FIGREF10" |
| } |
| ], |
| "eq_spans": [], |
| "section": "psr([slashM S], [slashLDb~, [slashRDS]); union( L D S, RD S, MS).", |
| "sec_num": null |
| }, |
| { |
| "text": "Then, the parser returns the parse tree and the category and constraint (c2()) of the top node. User solves the constraint to get the actual value of the variables. This is a parse tree of \"ai-suru hito\" that has two meaning: \"people whom someone loves\" or \"people who loves someone\". These ambiguity is shown in two solution of the constraint. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "psr([slashM S], [slashLDb~, [slashRDS]); union( L D S, RD S, MS).", |
| "sec_num": null |
| }, |
| { |
| "text": "In these earlier papers, \"constraint unification\" was called \"conditioned unification.\"", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
| "sec_num": null |
| } |
| ], |
| "back_matter": [ |
| { |
| "text": "This study owes much to our colleagues in the JPSG Working group at ICOT. The implementation of cu-Prolog is supported by ICOT and the Ministry of International Trade and Industry in Japan.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Acknowledgments", |
| "sec_num": null |
| } |
| ], |
| "bib_entries": { |
| "BIBREF0": { |
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| "raw_text": "The further study of cu-Prolog has many prospects.", |
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| "ref_entries": { |
| "FIGREF0": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "For example, mr(member(X, [a, b, d), member(X, [b, c, d]) ) returns a new constraint cO(X), where the definition of cO is cO(b). c0(c). and mr(member(X, [a, b, 4), member(X, [k, l, m]))" |
| }, |
| "FIGREF1": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "For example, X and Y are unifiable even after executing and freeze(X, member(X, [a, hi)) freeze(Y, member(Y, [u, v])) In cu-Prolog, and f(x); member(X, [a, hi). 2 I(Y); member(Y, [u, ,]). are not unifiable." |
| }, |
| "FIGREF2": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Let 7\" be definition clauses of modularly defined constraints, ~ be a set of constraints {C1,..., Cn} that contains variables zl, ... ,zm, and p be a new m-ary predicate. Let D be definition clauses of new predicates, and ~o = TU~) is initially {p(xl,..., xm): -C1,..., C,.} and other new predicates are included through the constraint normalization. Then, mf(~) returns p(zl,..., zm), if there exists a sequence of program clauses :P0, Pl,... ,~', and :Pn is modularly defined, where Pi+1 is derived from Pi (0 < i < n) by one of the following three types of transformations. 1. unfold transformation Select one clause C from Pi and one atomic for-mulaA from the body of C. Let C1, ..., Cn be all the clauses whose heads unify with A, and C~ be the result of applying Cj to A of C (j = 1,..., n). 7~+x is obtained by replacing C in :Pi with q,...,c-. :~rnember(X,[a,b D is not modular, but is equivalent to pI(X), where pl(~)." |
| }, |
| "FIGREF4": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "No variables occur in both K and L, and (b) C is not contained in 7)." |
| }, |
| "FIGREF5": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Here, T is { T1,T2,T3,T4 }, where T1 = member(X,[X[Y]).T2 = member(X,[Y[Z]):-member(X,Z). T3 = append([],X,X). T4 = append([AIX],Y,[AIZ]):-append(X,Y,Z).and E is {member(A, Z), append(X, Y, Z)}. The new predicate pl is defined as DI: p1(A,X,Y,Z):-member(A,Z),append(X,Y,Z). and P0 = {TI,T2,Z3,T4,D1},~ = {D1} Unfolding the first formula of Dl's body, we get T5 = pI(A,X,Y, [AIZ]) :-append(X,Y, [AIZ]). T6 = pI(A,X,Y, [BJZ]) :-member,(A,Z), append (X, Y, [B J Z/). So ~Pl --{T1,T2,T3,T4,TS,T6} By integration, T6' = pI(A,X,Y,[AJZ3):-p2(X,Y,A,Z). T6' = pI(A.X,Y,[BIZ3):-p3(A,Z,X,Y,B). D2 = p2(X,Y,A,Z):-append(X,Y, [AIZ]). D3 = p3(A,Z,X,Y,B):member (A, Z), append (X, Y, [B [ Z/). ([],[AIZ],A,Z)." |
| }, |
| "FIGREF6": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Figure" |
| }, |
| "FIGREF7": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "member(I,[IIY]). .member(I,[YlZ]):-member(I,Z). .append([],I,I). .append([lll],Y,[AIZ]):-append(X,Y,Z). .@ member(I,[ga,eo,nt]),member(X,[no,eo,nt]). solution = cO(I) cl(.o). cl(ni). cO(lO):-cl(IO). .@ member(A,l),append(I,Y,l). solution = cT(&, Z, I, Y) \u00a28(12, I2, IO, Yl, Y3):-append(IO, YI, Y3). c8(I2, Y3, IO, Y1, Z4):-c7(I2, Z4, XO, YI). cT(AO, Xl, D, II):-member(AO, I1). cT(Ao, [A%lz4], [A%lx2], Y3):-cB(AO, A1, I2, Y3, Z4).The first four lines are definitions of member and append. The lines that begin with \"(~\" are user's input atomic formulas (constraints). The system returns the constraint (cO(X)) that is equivalent to the input constraint, and its definitions." |
| }, |
| "FIGREF8": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Demonstration of the constraint transformation routine" |
| }, |
| "FIGREF9": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Demonstration of our 3PSG parser _ : -p ( [ai, suru, hit o] ). n In] : Semant ics.824---[adjunct_p] I [--v[Form_796, AJ|{n[h]}, $C{_820}]:Semmtics_824---[su~.pl I I I I--viva2, SC{Sc.376}1 : [love,Sbj_lE2,0bj.lS6]---[ai]" |
| }, |
| "FIGREF10": { |
| "type_str": "figure", |
| "num": null, |
| "uris": null, |
| "text": "Example of ambiguity" |
| }, |
| "TABREF3": { |
| "text": ". So the most difficult problem one must tackle concerns itself with heuristics about how to control computation. : -p ( [ken, ga ,naomi, wo, al, euru] ).", |
| "type_str": "table", |
| "html": null, |
| "content": "<table><tr><td colspan=\"2\">v [Form_764, AJ|{Adj_768}, SC{SubCat.772}] : SEN_776---[suff_p]</td></tr><tr><td colspan=\"2\">I [ --v [vs2, SC{Sc_752}] : [love, Sbj.120, Obj_1241 ---[subcat _p]</td></tr><tr><td colspan=\"2\">I l--pFga] :ken---[adjao.nt_p]</td></tr><tr><td>I I I</td><td>[ --n[n] :ken---[ken] I I__p[ga, AJA{n[n]}] :ken---[ga]</td></tr><tr><td colspan=\"2\">I l __v [vs2, SC{p [ga], $c_752}] : [love, Sbj_120,0bj_124] ---[subcat_p]</td></tr><tr><td/><td>I [ --p[wo] :naomi---[adjacent.p]</td></tr><tr><td/><td>I I [ l --n [hi :naomi---[naomi]</td></tr><tr><td/><td>I I [ I__p[wo, AJA{n[n]}] :naomi---[wo] I [__V[VS2, $C{p[wo], p[gal, Sc_752}] : [lovo,Sbj_120,Obj_124]---[ni]</td></tr><tr><td colspan=\"2\">[__v[For=_764, AJA{v[vs2,SC{Sc_752}]}, AJII{Adj_768}, SC{SubCat _772}1 : SEN.776---[suru]</td></tr><tr><td>cat</td><td>cat(v, Form_764, [], Adj.768, SubCat_772, SEH_776)</td></tr><tr><td>cond</td><td>[c2(Sc_752, 0bj_124, Sbj.120, Form_764, SubCat_772, Adj_768, SEM_776)]</td></tr><tr><td>True.</td><td/></tr><tr><td colspan=\"2\">. :-c2(.,_,_, F, SC, AD3 ,SEM).</td></tr><tr><td colspan=\"2\">F = syusi SC = [] ADJ ffi [] SEN = [love,ken,naomi]</td></tr></table>", |
| "num": null |
| }, |
| "TABREF4": { |
| "text": ":-c6(., ......... ,me=). inst(ObJO.136, [and, [people,ObJO_136], [love,SbJ1.140,ObjO_136]]) Sam : Inst (Sbj0.136, [and, Lpeople,SbJO_136], [lova,SbjO.t36,0bj1.140]])", |
| "type_str": "table", |
| "html": null, |
| "content": "<table><tr><td colspan=\"2\">I I I [ __n In] : inst (ObJ .932, [people, 0bj_932] )---[hit o] I I_.v[For=_796, AJA{v[vs2,$C{$\u00a2_376}]}, AJl{n[n]}, $(:{_820}1 :Semmtics.824---[surul</td></tr><tr><td>cat cond Title.</td><td>cat(n, n, [], [], [], Semantics.824) [c6($c_376, 0bj.156, $bj_152, Foz~.796, _820, 0bj.932, Semantics_824)1</td></tr><tr><td>Se~</td><td/></tr></table>", |
| "num": null |
| } |
| } |
| } |
| } |
