ACL-OCL / Base_JSON /prefixP /json /P91 /P91-1033.json
Benjamin Aw
Add updated pkl file v3
6fa4bc9
{
"paper_id": "P91-1033",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T09:03:35.621850Z"
},
"title": "LOGIC WITH WEAK SUBSUMPTION CONSTRAINTS",
"authors": [
{
"first": "Jochen",
"middle": [],
"last": "Dbere",
"suffix": "",
"affiliation": {
"laboratory": "",
"institution": "IBM Deutschland OmbH Science Center -IKBS",
"location": {
"postBox": "P.O. Box 80 08 80",
"postCode": "D-7000",
"settlement": "Stuttgart 80",
"country": "Germany"
}
},
"email": ""
}
],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "In the general framework of a constraint-based grammar formalism often some sort of feature logic serves as the constraint language to describe linguistic objects. We investigate the extension of basic feature logic with subsumption (or matching) constraints, based on a weak notion of subsumption. This mechanism of oneway information flow is generally deemed to be necessary to give linguistically satisfactory descriptions of coordination phenomena in such formalisms. We show that the problem whether a set of constraints is satisfiable in this logic is decidable in polynomial time and give a solution algorithm.",
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"paper_id": "P91-1033",
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"abstract": [
{
"text": "In the general framework of a constraint-based grammar formalism often some sort of feature logic serves as the constraint language to describe linguistic objects. We investigate the extension of basic feature logic with subsumption (or matching) constraints, based on a weak notion of subsumption. This mechanism of oneway information flow is generally deemed to be necessary to give linguistically satisfactory descriptions of coordination phenomena in such formalisms. We show that the problem whether a set of constraints is satisfiable in this logic is decidable in polynomial time and give a solution algorithm.",
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"section": "Abstract",
"sec_num": null
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"text": "Many of the current constralnt-based grammar formalisms, as e.g. FUG [Kay 79, Kay 85] , LFG [Kaplan/Bresnan 82], HPSG [Pollard/Sag 87] , and its derivates, model linguistic knowledge in recursive feature structures. Feature (or functional) equations, as in LFG, or feature terms, as in FUG or STUF [Bouma et al. 88] , are used as constraints to describe declaratively what properties should be assigned to a linguistic entity. In the last few years, the study of the forreal semantics and formal properties of logics involving such constraints has made substantial progress [Kasper/Rounds 86, Johnson 87, Smolka 88, Smolka 89 ], e.g., by making precise which sublanguages of predicate logic it corresponds to. This paves the way not only for reliable implementations of these formalisms, but also for extensions of the basic logic with a precisely defined meaning. The extension we present here, weak subsumption constraints, is a mechanism of one-way information flow, often proposed for a logical treatment of coordination in a feature-based unification grammar. 1 It can I Another application would be type inference in a grammar formalism (or programming language) that be informally described as a device, which enables us to require that one part of a (solution) feature structure has to be subsumed (be an instance of) another part. Consider the following example of a coordination with \"and\", taken from [Shieber 89]. Clearly (2) is ungrammatical since the verb \"hire\" requires a noun phrase as object complement and this requirement has to be fulfilled by both coordinated complements. This subcategorization requirement is modeled in a unification-based grammar generaUy using equations which cause the features of a complement (or parts thereof encoding the type) to get unified with features encoding the requirements of the respective position in the subcategorization frame of the verb. Thus we could assume that for a coordination the type-encoding features of each element have to be \"unified into\" the respective position in the subcategorisation frame. This entails that the coordinated elements are taken to be of one single type, which then can be viewed as the type of the whole coordination. This approach works fine for the verb \"hire\", but certain verbs, used very frequently, do not require this strict identity. The verb \"become\" may have either nounphrase or adjective-phrase complements, \"to be\" Mlows prepositional and verb phrases in addition, and these may appear intermixed in a coordination. In order to allow for such \"polymorphic\" type requirements, we want to l~e~ a-type discipline with polymorphic types. state, that (the types of) coordinated arguments each should be an instance of the respective requirement from the verb. Expressed in a general rule for (constituent) coordination, we want the structures of coordinated phrases to be instances of the structure of the coordination. Using subsumption constraints the rule basically looks like this:",
"cite_spans": [
{
"start": 69,
"end": 77,
"text": "[Kay 79,",
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{
"start": 78,
"end": 85,
"text": "Kay 85]",
"ref_id": null
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{
"start": 118,
"end": 134,
"text": "[Pollard/Sag 87]",
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{
"start": 298,
"end": 315,
"text": "[Bouma et al. 88]",
"ref_id": null
},
{
"start": 574,
"end": 592,
"text": "[Kasper/Rounds 86,",
"ref_id": null
},
{
"start": 593,
"end": 604,
"text": "Johnson 87,",
"ref_id": null
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{
"start": 605,
"end": 615,
"text": "Smolka 88,",
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{
"start": 616,
"end": 625,
"text": "Smolka 89",
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],
"ref_spans": [],
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"section": "Introduction",
"sec_num": "1"
},
{
"text": "E ~ C and D",
"cite_spans": [],
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"eq_spans": [],
"section": "Introduction",
"sec_num": "1"
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{
"text": "With an encoding of the types like the one proposed in HPSG we can model the subcategorisation requirements for\"to be\" and \"to become\" as generalizations of all allowed types (cf. where the coordinated elements are required to be in a set of feature structures and where the feature structure of the whole set is defined as the generalisation (greatest lower bound w.r.t. subsumption) of its elements. This entails the requirement stated above, namely that the structure of the coordination subsumes those of its elements. In fact, it seems that especially in the context of set-valued feature structures (cf.",
"cite_spans": [],
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"section": "E~C E~D",
"sec_num": null
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{
"text": "[Rounds 88]) we need some method of inheritance of constraints, since if we want to state general combination rules which apply to the set-valued objects as well, we would like constraints imposed on them to affect also their members in a principled way. Now, recently it turned out that a feature logic involving subsumption constraints, which are based on the generally adopted notion of subsumption for feature graphs is undecidable (cf.",
"cite_spans": [],
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"section": "E~C E~D",
"sec_num": null
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{
"text": "[D rre/Rounds 90]). In the present paper we therefore investigate a weaker notion of subsumption, which we can roughly characterize as relaxing the constraint that an instance of a feature graph contains all of its path equivalencies. Observe, that path equivalencies play no role in the subcategorisation requirements in our examples above ...... ~",
"cite_spans": [],
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"section": "E~C E~D",
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"text": "In this section we define the basic structures which are possible interpretations of feature descriptions, the expressions of our feature logic. Instead of restricting ourselves to a specific interpretation, like in [Kasper/Rounds 86] where feature structures are defined as a special kind of finite automata, we employ an open-world semantics as in predicate logic. We adopt most of the basic definitions from [Smolka 89 ]. The mathematical structures which serve us as interpretations are called feature algebras. We begin by assuming the pairwise disjoint sets of symbols L, A and V, called the sets of features (or labels), atoms (or constants) and variables, respectively. Generally we use the letters /,g, h for features, a, b, c for atoms, and z, ~, z for variables. The letters s and t always denote variables or atoms. We assume that there are infinitely many variables. Notation. We write function symbols on the right following the notation for record fields in computer languages, so that f(d) is written dr. If f is defined at d, we write d.f ~, and otherwise d/ T. We use p,q,r to denote strings of features, called paths. The interpretation function .Jr is straightforwardly extended to paths: for the empty path e, ~.4 is the identity on D~4; for a path p = fl ... f-, p~4 is the unary partial function which is the composition of the filnctions fi\"4.., f.4, where .fl \"4 is applied first. A feature algebra of special interest is the Feature Graph Algebra yr since it is canonical in the sense that whenever there exists a solution for a formula in basic feature logic in some feature algebra then there is also one in the Feature Graph Algebra. The same holds if we ex-tend our logic to subsumption constraints (see ~DSrre/Rounds 90]). A feature graph is a rooted and connected directed graph. The nodes are either variables or atoms, where atoms may appear only as terminal nodes. The edges are labeled with features and for every node no two outgoing edges may be labeled with the same feature. We formalize feature graphs as pairs (s0, E) where So E VUA is the root and E C V x L x (V U A) is a set of triples, the edges. The following conditions hold:",
"cite_spans": [
{
"start": 216,
"end": 234,
"text": "[Kasper/Rounds 86]",
"ref_id": null
},
{
"start": 411,
"end": 421,
"text": "[Smolka 89",
"ref_id": null
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],
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"section": "Feature Algebras",
"sec_num": "2"
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{
"text": "1. If s0EA, thenE=0. 2. If (z, f, s) and (z, f, t) are in E, then s : t. 3. If (z, f, 8) is in E, then E contains edges leading from the root s0 to the node z.",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "Let G -(z0, E) be a feature graph containing an edge (z0, f, s). The subgraph under f of G (written G/f) is the maximal graph (s, E') such that E t C E. Now it is clear how the Feature Graph Algebra ~\" is to be defined. D ~r is the set of all feature graphs. The interpretation of an atom a ~r is the feature graph (a, ~), and for a feature f we let G.f 7~ = G/.f, if this is defined. It is easy to verify that ~r is a feature algebra. Feature graphs are normally seen as data objects containing information. From this viewpoint there exists a natural preorder, called subsumptlon preorder, that orders feature graphs according to their informational content thereby abstracting away from variable names. We do not introduce subsumption on feature graphs here directly, but instead we define a subsumption order on feature algebras in general. Let .A and B be feature algebras. A simulation between .A and B is a relation A C D ~4 \u00d7 D v satisfying the following conditions:",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "1. if (a ~4, d) E A then d = a B, for each atom a, and 2. for any d E D~,e E D B and f E L: if df A ~ and (d,e) E A, then ef B ~ and",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "(dr ~4, ef B) E A.",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "Notice that the union of two simulations and the transitive closure of a simulation are also simulations. A partial homomorphlsm \"y between .A and B is a simulation between the two which is a partial function. If.A = B we also call T a partial endomorphism. Definition. Let .A be a feature algebra. The (strong) subsumption preorder ff_A and the weak subsumption preorder ~4 of ~4 are defined as follows:",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "* d (strongly) subsumes e (written d E ~4 e)",
"cite_spans": [],
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"eq_spans": [],
"section": "Feature Algebras",
"sec_num": "2"
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"text": "iff there is an endomorphism \"y such that = e. * d wealcly subsumes e (written d ~4 e) iff there is a simulation A such that dAe.",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "It can be shown (see [Smolka 89] ) that the subsumption preorder of the feature graph algebra coincides with the subsumption order usually defined on feature graphs, e.g. in [Kasper/Rounds 86] .",
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{
"start": 21,
"end": 32,
"text": "[Smolka 89]",
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"start": 174,
"end": 192,
"text": "[Kasper/Rounds 86]",
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "Example: Consider the feature algebra depicted in Fig. 2 , which consists of the elements {1, 2, 3, 4, 5, a, b) where a and b shall be (the pictures of) atoms and f, g, i and j shall be features whose interpretations are as indicated.",
"cite_spans": [],
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{
"start": 50,
"end": 56,
"text": "Fig. 2",
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],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "i i\u2022 simulation A f g 1A3 2A4 2A5 aAa bAb a a b",
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"section": "Feature Algebras",
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"text": "Figure 2: Example of Weak Subsumption Now, element 1 does not strongly subsume 3, since for 3 it does not hold, that its f-value equals its g-value. However, the simulation A demonstrates that they stand in the weak subsumption relation: 1 ~ 3.",
"cite_spans": [],
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"section": "Feature Algebras",
"sec_num": "2"
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"text": "To describe feature algebras we use a relational language similar to the language of feature descriptions in LFG or path equations in PATR-II. Our syntax of constraints shall allow for the forms zp \"----~q, zp \"----a, zp ~ ~q where p and q are paths (possibly empty), a E A, and z and ~/are variables. A feature clause is a finite set of constraints of the above forms.",
"cite_spans": [],
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"section": "Constraints",
"sec_num": "3"
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"text": "As usual we interpret constraints with respect to a variable assignment, in order to make sure that variables are interpreted uniformly in the whole set. An assignment is a mapping ~ of variables to the elements of some feature alge-bra. A constraint ~ is satisfied in .,4 under assignment a, written (A, a) ~ ~, as follows:",
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"section": "Constraints",
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"text": "(.,4, a) ~ zp -vq iff a(z)p A = a(v)q A (.4, a) ~ zp --a aft a(z)p A if (v)qA.",
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"section": "Constraints",
"sec_num": "3"
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"text": "The solutions of a clause C in a feature algebra .4 are those assignments which satisfy each constraint in C. Two clauses C1 and C2 are equivalent iff they have the same set of solutions in every feature algebra .A. The problem we want to consider is the following:",
"cite_spans": [],
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"section": "Constraints",
"sec_num": "3"
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"text": "Given a clause C with symbols from V, L and A, does C have a solution in some feature algebra?",
"cite_spans": [],
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"section": "Constraints",
"sec_num": "3"
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"text": "We call this problem the weak semiunification problem in feature algebras)",
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"section": "Constraints",
"sec_num": "3"
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"text": "4 An Algorithm",
"cite_spans": [],
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"section": "Constraints",
"sec_num": "3"
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"text": "We give a solution algorithm for feature clauses based on normalization, i.e. the goal is to define a normal form which exhibits unsatisfiability and rewrite rules which transform each feature clause into normal form. The normal form we present here actually is only half the way to a solution, but we show below that with the use of a standard algorithm solutions can be generated from it. First we introduce the restricted syntax of the normal form. Clauses containing only constraints of the following forms are called simple:",
"cite_spans": [],
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "zf --y, z--s, z ~ y",
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "where s is either a variable or an atom. Each feature clause can be restated in linear time as an equisatisfiable simple feature clause whose solutions are extensions of the solutions of the original clause, through the introduction of auxiliary variables. This step is trivial.",
"cite_spans": [],
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "A feature clause C is called presolved iff it is simple and satisfies the following conditions. ~The anMogous problem for (strong) subsumption constraints is undecidable, even if we restrict ourselves to finite feature algebras. Actually, this problem could be shown to be equivalent to the semiunification problem for rational trees, i.e. first-order terms which may contain cycles. The interested reader is referred to [D~rre/Rounds 90].",
"cite_spans": [],
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"sec_num": "4.1"
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"text": "C1. If z -~/is in C, then z occurs exactly once in C. C2. Ifzf-yandzf-zareinC, theny=z. C3. Ifz~vandy~zareinC, thenz~zis in C (transitive closure). C4. Ifz ~V and z f--z t and Vf --V t are in C, then z' ~ V' is in C (downward propagation closure).",
"cite_spans": [],
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "In the first step our algorithm attempts to transform feature clauses to presolved form, thereby solving the equational part. In the simplification rules (cf. Fig. 3 ) we have adapted some of Smolka's rules for feature clauses including complements [Smolka 89 ]. In the rules [z/s]C denotes the clause C where every occurrence of z has been replaced with s, and ~ & C denotes the feature clause {~} U C provided ~b ~ C.",
"cite_spans": [
{
"start": 249,
"end": 259,
"text": "[Smolka 89",
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],
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{
"start": 159,
"end": 165,
"text": "Fig. 3",
"ref_id": "FIGREF1"
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],
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "Theorem 1 Let C be a simple feature clause. Then I. if C can be rewritten to 19 using one of the rules, then 1) i8 a simple feature clause equivalent to C, f. for every non-normal simple feature clause one of the rewrite rules applies, 3. there is no infinite chain C --* U1 --* C2 --, ProoL 3 The first part can be verified straightforwardly by inspecting the rules. The same holds for the second part. To show the termination claim first observe that the application of the last two rules can safely be postponed until no one of the others can apply any more, since they only introduce subsumption constraints, which cannot feed the other rules. Now, call a variable z isolated in a clause C, if C contains an equation z -7/and z occurs exactly once in C. The first rule strictly increases the number of isolated variables and no rule ever decreases it. Application of the second and third rule decrease the number of equational constraints or the number of features appearing in C, which no other rule increase. Finally, the last two rules strictly increase the number of subsumption constraints for a constant set of variables. Hence, no infinite chain of rewriting steps may be produced.",
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"section": "Presolved Form",
"sec_num": "4.1"
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"text": "[] We will show now, that the presolved form can be seen as a nondeterministic finite automaton with e-moves and that we can read off solutions from its deterministic equivalent, if that is of a special, trivially verifiable, form, called clashbee.",
"cite_spans": [],
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"section": "Presolved Form",
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"text": "The intuition behind this construction is, that subsumption constraints basically enfoice that information about one variable (and the space teachable hom it) has to be inherited by (copied to) another variable. For example the constraints z H y and zp -a entail that also lip -a has to hold. 4 Now, if we have a constraint z ~ T/, we could think of actually copying the information found under z to y, e.g. zf -z ~ would be copied to 1/f -1/t, where 1/I is a new variable, and z I would be linked to yl by z p ~ ?/. However, this treatment is hard to control in the presence of cycles, which always can occur. Instead of actually copying we also can regard a constraint z g 7/as a pointer \u00a2rom ~ back to z leading us to the information which is needed to construct the local solution of ~. To extend this view we regard the whole p~esolved chase C as a finite automaton: take variables and atoms as nodes, a feature constraint as an arc labeled with the feature, constraints z -s and 1/~ z as e-moves horn z to s or ~/. We can show then that C is unsatisfiable iff there is some z hom which we reach atom a via path p such that we can also reach b(~ a) via p or there is a path starting from z whose proper prefix is p. Formally, let NFA Arc of presolved clause C be ~F~rora this point of view the difference between weak and strong subsumption can be captured in the type of information they enforce to be inherited. Strong subsumption requires path equivalences to be inherited (x ~ y and ~p -\" zq implies yp -yq), whereas weak subsumption does not. ",
"cite_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
},
{
"text": "I \u2022 g c} u f, I -\" c} v \u2022 c}",
"cite_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
},
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"text": "As usual, let ~c be the extension of 6c to paths.",
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"ref_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
},
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"text": "Notice that zpa E L(Afc) iff (z,p,a) E ~c. The language accepted by this automaton contains strings of the forms zp or zpa, where a string zp indicates that in a solution a the object ol(z)p ~t should be defined and zpa tells us further that this object should be a A. A set of strings of (",
"cite_spans": [],
"ref_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
},
{
"text": "V x L*) U (V x L* x A)",
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"ref_spans": [],
"eq_spans": [],
"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
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"text": "is called clash-free iff it does not contain a string zpa together with zpb (where a ~ b) or together with zpf. It is clear that the property of a regular language L of being dash-free with respect to L and A can be read off immediately from a DFA D for it: if D contains a state q with 5(q, a) E F and either 6(q, b) E F (where a ~ b) or 6(q, f) E F, then it is not clash-free, otherwise it is. We now present our centrM theorem. Proof. see Appendix A. Now the algorithm consists of the following simple or well-understood steps:",
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
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"text": "1: (a) Solve the equationai constraints of C, which can be done using standard unification methods, exemplified by rules 1) to 3).",
"cite_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
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"text": "(b) Make the set of weak subsumption constraints transitively and \"downward\" closed (rules 4) and 5)). 2: The result interpreted as an NFA is made deterministic using standard methods and tested of being clash-free.",
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"ref_spans": [],
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"section": "The Transition Relation 6c of a Presolved Clause C",
"sec_num": "4.2"
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"text": "For the purpose of proving the algorithm correct it was easiest to assume that clash-freeness is determined after transforming the NFA of the presolved form into a deterministic automaton. However, this translation step has a time complexity which is exponential with the number of states in the worst case. In this section[A we consider a technique to determine clash-freeness directly from the NFA representation of the presolved form in polynomial time. We do not go into implementational details, though. Instead we are concerned to describe the different steps more from a logical point of view. It can be assumed that there is still room left for optimizations which improve ef[iciency.",
"cite_spans": [],
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"eq_spans": [],
"section": "Determining Clash-Freeness Directly",
"sec_num": "4.3"
},
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"text": "In a first step we eliminate all the e-transitions from the NFA Arc-We will call the result still Arc. For every pair of a variable node z and an atom node a let Arc[z,a] be the (sub-)automaton of all states of Arc reachable horn z, but with the atom a being the only final state. Thus, Afc[z,g] accepts exactly the language of all strings p for which zpg E L(Arc).",
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"section": "Determining Clash-Freeness Directly",
"sec_num": "4.3"
},
{
"text": "Likewise, let Afc[z,~] be the (sub-)automaton of all states olaf C reachable from z, but where every atom node besides a is in the set of final states as well as every node with an outgoing feature arc. The set accepted by this machine contains every string p such that zpb E L(ArC), (b ~ a) or zpf E L(Arc). If and only if the intersection of these two machines is empty for every z and a, L(Arc) is clash-free.",
"cite_spans": [
{
"start": 284,
"end": 291,
"text": "(b ~ a)",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Determining Clash-Freeness Directly",
"sec_num": "4.3"
},
{
"text": "Let us now examine the complexity of the different steps of the algorithm. We know that Part la) can be done (using the efficient union/find technique to maintain equivalence classes of variables and vectors of features for each representative) in nearly linear time, the result being smaller or of equal size than Co. Part lb) may blow up the clause to a size at most quadratic with the number of different variables n, since we cannot have more subsumption constraints than this. For every new subsumption constraint, trying to apply ruh 4) might involve at most 2n membership test to check whether we are actually adding a new constraint, whereas for rule 5) this number only depends on the size of L. Hence, we stay within cubic time until here. Determining whether the presolved form is dash-free from the NPA representation is done in three steps. The e-free representation of Arc does not increase the number of states. If n,a and l are the numbers of variables, atoms and features resp. in the initial clause, then the number of edges is in any case smaller than (n + a) ~ \u2022 l, since there are only n + a states. This computation can be performed in time of an order less than o((~z + a)3). Second, we have to build the intersections for Arc [z,a] and Arc [z,g] for every z and a. Intersection of two NFAs is done by building a crossproduct machine, requiring maximally o((~z + a) 4 \u2022 l) time and space. \u00a2 The test for emptiness of these intersection machines is again trivial and can be performed in constant time. Hence, we estimate a total time and space complexity of order n-a. (Tz + a) 4 \u2022 I.",
"cite_spans": [
{
"start": 1250,
"end": 1255,
"text": "[z,a]",
"ref_id": null
},
{
"start": 1264,
"end": 1269,
"text": "[z,g]",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Complexity",
"sec_num": "4.4"
},
{
"text": "7This is an estimate for the number of edges, since the nmuber of states is below (n + a) 2. As usual, we assume appropriate data structures where we can neglect the order of access times. Probably the space (and time) complexity can be reduced hrther, since we actually do not need the representations of the intersection machines besides for testing, whether they can accept anything.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Complexity",
"sec_num": "4.4"
},
{
"text": "We proposed an extension to the basic feature logic of variables, features, atoms, and equational constraints. This extension provides a means for one-way information passing. We have given a simple, but nevertheless completely formal semantics for the logic and have shown that the satisfiability (or unification) problem in the logic involving weak subsumption constraints is decidable in polynomial time. Furthermote, the first part of the algorithm is a surprisingly simple extension of a standard unification algorithm for feature logic. We have formulated the second part of the problem as a simple property of the regular language which the outcome of the first part defines. Hence, we could make use of standard techniques from automata theory to solve this part of the problem. The algorithm has been proved to be correct, complete, and guaranteed to terminate. There are no problems with cycles or with infinite chains of subsumption relations as generated by a constraint like z ~ zf. s",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "The basic algorithmic requirements to solve the problem being understood, the challenge now is to find ways how solutions can be found in a more incremental way, if we already have solutions for subsets of a clause. To achieve this we plan to amalgamate more closely the two parts algorithms, for instance, through implementing the check for clash-freeness also with the help of (a new form of) constraints. It would be interesting also from a theoretical point of view to find out how much of the complexity of the second part is really necessary. Now let the elements of the dommn be, besides interpretations of atoms, just those objects (partial functions) which can be reached by application of some features to some a(z).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "\u2022 DA = {a(z)q \"41 =eVe, q\u2022L'} u {.-~ IaeA}.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "To see that D ~t is finite, we first observe that the domain of each a(z) is a regular set ({Pl zpaEA/'v, aEA}) and the range is finite. Now, for a regular set R call {p [ qp\u2022R} the suffix language of R with respect to string q. It is clear, that there are only finitely many suit-ix languages, since each corresponds to one state in the minimal finite automaton for R. But then also the number of partial functions \"reachable\" from an a(z) is finite, since the domain of a(z)q \"4 is a suffix language of the domain of a(=).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "We now show that given 17 the model (.A~ c~) satisfies all constraints in C.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "\u2022 Ifm \"--a \u2022 C: za e Z~(Afc) ~ (,,a) e o,(z).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "Now we know from I) that no other pair is in a(=), i.e. a(z) = a \"a. (y',p,a) \u2022 5c, i.e. z' is the last state before f is consumed on a path consuming .fpa. But now, since emoves on such a chain correspond to subsumption constraints (none of the variables in the cltain is isolated) and since C is transitively closed for subsumption constraints, C has to contain a constraint z' ~ z. But the last condition for normal form now tells us, that also y' ~ y is in C, implying (y,e,V') \u2022 5c. In order to show the other direction let us first show a property needed in the proof.",
"cite_spans": [],
"ref_spans": [
{
"start": 69,
"end": 77,
"text": "(y',p,a)",
"ref_id": null
}
],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "Lemma 1 /f (.A, a) is a model/or presol~ed elaase c ,,.,t (=,p, s) e ,~c, the. o,(s) ~a ,.(,~) pa. (z! s = a let ez(a) = a A/or this p~trpose.)",
"cite_spans": [],
"ref_spans": [
{
"start": 11,
"end": 95,
"text": "(.A, a) is a model/or presol~ed elaase c ,,.,t (=,p, s) e ,~c, the. o,(s) ~a ,.(,~)",
"ref_id": null
}
],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "Proof. We show by induction over the defmltion of 5c that, given the condition above, there exists a simulation a in .,4 such that a(s)Aa(z)p'4.. As in case 1) we have ~(z)pjt __ aA. Ffonl which entails that ].4 has to be defined for ~(z)p.4, a contradiction.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "This completes the proof.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
},
{
"text": "[]",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "5"
}
],
"back_matter": [
{
"text": "I am indebted to Bill Romtds for reading a first draft of this paper and pointing out to me a way to test dash-freeness in polynomial time. Of course, any remaining errors are those of the author. I would also llke to thank Gert Smolka for giving valuable comments on the first draft.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Acknowledgment",
"sec_num": null
},
{
"text": "Appendix A: Proof of Theorem 2 From Theorem I we know that C is equivalent to Co, i.e. it suffices to show the theorem for the existence of solutions of C in 2) and 3). Since 2) =~ 3) is obvious, it remains to show 1) =~ 2) and 3 7 ::~ 1). 1) ~ 2): We construct a finite model (\u00a24, a) whose domain contains partial functions from paths to atoms (D A C L*-+ A). Interpretation and variable assignment are given as follows:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "annex",
"sec_num": null
}
],
"bib_entries": {
"BIBREF0": {
"ref_id": "b0",
"title": "Gosse Bouma, Esther K~nig and Hans Uszkoreit. A flexible graph-lmification forrealism and its application to natural-language processing",
"authors": [],
"year": 1988,
"venue": "IBM Journal of Research and Development",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "References [Bouma et at. 88] Gosse Bouma, Esther K~nig and Hans Uszkoreit. A flexible graph-lmification for- realism and its application to natural-language processing. In: IBM Journal of Research and De- velopment, 1988.",
"links": null
},
"BIBREF1": {
"ref_id": "b1",
"title": "Lexleal Functional Granunar: A Forreal System for Grammatical Representation",
"authors": [
{
"first": "C",
"middle": [],
"last": "Ssee ; Jochen D~rre And Willimn",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Rounds ; Mark Jolmson ; Ronald",
"suffix": ""
},
{
"first": "Joan",
"middle": [],
"last": "Kaplan",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Bresnan",
"suffix": ""
}
],
"year": 1982,
"venue": "Proceedings of the 5th Annual Symposium on Logic in Computer Science",
"volume": "16",
"issue": "",
"pages": "300--310",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "SSee [$hieber 89] for a discussion of this problem. [D~rre/Rounds 90] Jochen D~rre and Willimn C. Rounds. On Subsuraption and Seminnification in Feature Algebras. In Proceedings of the 5th An- nual Symposium on Logic in Computer Science, pages 300-310, Philadelphia, PA., 1990. Also ap- pears in: Journal of Symbolic Computation. [Johnson 87] Mark Jolmson. Attribute-Value Logic and the Theory of Grammar. CSLI Lecture Notes 16, CSLI, Stanford University, 1987. [Kaphm/Bresnan 82] Ronald M. Kaplan and Joan Bresnan. Lexleal Functional Granunar: A For- real System for Grammatical Representation. In: J. Bresnan (ed.), The Mental Representation o] Grammatical Relations. MIT Press, Cambridge, Massachusetts, 1982.",
"links": null
},
"BIBREF2": {
"ref_id": "b2",
"title": "Constituent Coordination in Lexieal-Functional Grammar",
"authors": [
{
"first": "M",
"middle": [],
"last": "Kaplan ; Ronald",
"suffix": ""
},
{
"first": "John",
"middle": [
"T"
],
"last": "Kaplan",
"suffix": ""
},
{
"first": "H",
"middle": [
"I"
],
"last": "Maxwell",
"suffix": ""
}
],
"year": null,
"venue": "Proc. o] COL",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Kaplan/Maxwell 88] Ronald M. Kaplan and John T. Maxwell HI. Constituent Coordination in Lexieal-Functional Grammar. In: Proc. o] COL.",
"links": null
},
"BIBREF4": {
"ref_id": "b4",
"title": "A Logical Semantics for Feature Structures",
"authors": [
{
"first": "Robert",
"middle": [
"T"
],
"last": "Kasper",
"suffix": ""
},
{
"first": "Williant",
"middle": [
"C"
],
"last": "Kasper",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Rounds",
"suffix": ""
}
],
"year": 1986,
"venue": "Proceedings o] the ~th Annual Meeting o] the A CL",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Kasper/Rounds 86] Robert T. Kasper and Williant C. Rounds. A Logical Semantics for Feature Structures. In: Proceedings o] the ~th Annual Meeting o] the A CL. Columbia University, New York, NY, 1986.",
"links": null
},
"BIBREF5": {
"ref_id": "b5",
"title": "Proceedings o] the 5th Annual Meeting o] the Berkeley Linguistic Society",
"authors": [
{
"first": "Martin",
"middle": [],
"last": "Kay",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Grmnmar",
"suffix": ""
}
],
"year": 1979,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Martin Kay. Functional Grmnmar. In: C. Chiarello et al. (eds.) Proceedings o] the 5th An- nual Meeting o] the Berkeley Linguistic Society. 1979.",
"links": null
},
"BIBREF6": {
"ref_id": "b6",
"title": "Parsing in Functional Unification Grammar",
"authors": [
{
"first": "Martin",
"middle": [],
"last": "Kay",
"suffix": ""
}
],
"year": 1985,
"venue": "Natural Language Parsing",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Martin Kay. Parsing in Functional Unifi- cation Grammar. In: D. Dowry, L. Karttunen, and A. Zwieky (eds.) Natural Language Parsing, Cambridge, England, 1985",
"links": null
},
"BIBREF7": {
"ref_id": "b7",
"title": "ormation-Based Syntax and Semantics, Voi. 1. CSLI Lecture Notes 13, CSLI, Stanford University",
"authors": [
{
"first": "Carl",
"middle": [],
"last": "Pollard",
"suffix": ""
},
{
"first": "Ivan",
"middle": [
"A"
],
"last": "Sag",
"suffix": ""
}
],
"year": 1987,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "[Pollard/Sag 87] Carl Pollard and Ivan A. Sag. In]ormation-Based Syntax and Semantics, Voi. 1. CSLI Lecture Notes 13, CSLI, Stanford Uni- versity, 1987.",
"links": null
},
"BIBREF8": {
"ref_id": "b8",
"title": "Set Values for Unification-Based Grammar Formalisms and Logic Programming",
"authors": [
{
"first": "C",
"middle": [],
"last": "William",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Rounds",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Stuart",
"suffix": ""
},
{
"first": "Hans",
"middle": [],
"last": "Shiebcr",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Uszkoreit",
"suffix": ""
},
{
"first": "C",
"middle": [
"N"
],
"last": "Fernando",
"suffix": ""
},
{
"first": "J",
"middle": [
"J"
],
"last": "Perelra",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Robinson",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Tyson",
"suffix": ""
}
],
"year": 1983,
"venue": "Research on Interactive Acquisition and Use o] Knowledge, SRI International",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "William C. Rounds. Set Values for Unification-Based Grammar Formalisms and Logic Programming. CSLI-Report 88-129, CSLI, Stanford University, 1988. [Shieber et al. 83] Stuart M. Shiebcr, Hans Uszko- reit, Fernando C.N. Perelra, J.J. Robinson, M. Tyson. The formalism and implementation of PATR-II. In: J. Bresnan (ed.), Research on In- teractive Acquisition and Use o] Knowledge, SRI International, Menlo Park, CA, 1983.",
"links": null
},
"BIBREF9": {
"ref_id": "b9",
"title": "Parsing and Type Inference for Nahtral and Computer Languages",
"authors": [
{
"first": "M",
"middle": [],
"last": "Stuart",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Shieber",
"suffix": ""
}
],
"year": 1989,
"venue": "SRI International",
"volume": "460",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Stuart M. Shieber. Parsing and Type Inference for Nahtral and Computer Languages. Technical Note 460, SRI International, Meldo Park, CA, March 1989.",
"links": null
},
"BIBREF10": {
"ref_id": "b10",
"title": "A Feature Logic with 5ub-sorts",
"authors": [
{
"first": "Gert",
"middle": [],
"last": "Smolka",
"suffix": ""
},
{
"first": ";",
"middle": [],
"last": "Iwbs",
"suffix": ""
},
{
"first": "W",
"middle": [],
"last": "Deutschland",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Germany",
"suffix": ""
}
],
"year": 1988,
"venue": "",
"volume": "33",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Gert Smolka. A Feature Logic with 5ub- sorts. LILOG-Report 33, IWBS, IBM Deutsch- land, W. Germany, May 1988. To appear in the Journal of Automated Reasoning.",
"links": null
},
"BIBREF11": {
"ref_id": "b11",
"title": "Feature Constraint Logics ]or Unification Grammars. I",
"authors": [
{
"first": "Gert",
"middle": [],
"last": "Smollm",
"suffix": ""
},
{
"first": ";",
"middle": [],
"last": "Iwbs",
"suffix": ""
},
{
"first": "W",
"middle": [],
"last": "Deutschland",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Germany",
"suffix": ""
}
],
"year": 1989,
"venue": "Proceedings of the Workshop on Unification Formalisms--Syntax, Semantics and Implementation",
"volume": "93",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Gert Smollm. Feature Constraint Log- ics ]or Unification Grammars. I\"WBS Report 93, IWBS, IBM Deutschland, W. Germany, Nov. 1989. To appear in the Proceedings of the Work- shop on Unification Formalisms--Syntax, Se- mantics and Implementation, Titisee, The MIT Press, 1990.",
"links": null
}
},
"ref_entries": {
"FIGREF0": {
"uris": null,
"text": "Pat hired [tcP a Republican] and [NP a banker]. (2) *Pat hired [NP a Republican] and lAP proud of it].",
"type_str": "figure",
"num": null
},
"FIGREF1": {
"uris": null,
"text": "Pat has become [NP a banker] and [AP very conservative]. (4) Pat is lAP healthy] and [pp of sound mind].",
"type_str": "figure",
"num": null
},
"FIGREF2": {
"uris": null,
"text": "Encoding of syntactic type A similar treatment of constituent coordination has been proposed in [Kaplan/Maxwell 88],",
"type_str": "figure",
"num": null
},
"FIGREF3": {
"uris": null,
"text": "feature algebra .A is a pair (D ~4, ..4) consisting of a nonempty set D ~t (the domain of.4) and an interpretation .~ defined on L and A such that * a ~4 E D \"4 for a E A. (atoms are constants) \u2022 Ifa ~ b then a \"4 ~ b ~4. (unique name assumption) \u2022 If f is a feature then/~4 is a unary partial function on D ~4. (features are functional) \u2022 No feature is defined on an atom.",
"type_str": "figure",
"num": null
},
"FIGREF4": {
"uris": null,
"text": "~Part of this proof has been directly adapted from[S molka 89]. Rewriting to presolved form",
"type_str": "figure",
"num": null
},
"FIGREF5": {
"uris": null,
"text": "defined as follows. Its states are the variables occurring in C (Vc) plus the atoms plus the states qF and the initial state q0. The set of final states is Vc U {qp}. The alphabet of Arc is vcu z, u A u {e}. 5 The transition relation is defined as follows: s 6c := vc} o {(a,a,q~)la~ A} u",
"type_str": "figure",
"num": null
},
"FIGREF6": {
"uris": null,
"text": "every atom a (the function mapping only the empty string to a) \u2022 for every ] \u2022 L,X \u2022 L*--M: X] \"4 = {(p, a)I (Yp, a) \u2022 x} \u2022 a(w) = {(p,a) lzpa \u2022L(Afc)}, which is apartial function, due to 1 ).",
"type_str": "figure",
"num": null
},
"FIGREF7": {
"uris": null,
"text": "\u2022 If m -y \u2022 C: Since = occurs only once in C, the only transition from z is (z, e, y), thus (=,p,a) \u2022 ~c m (V,p,a) \u2022 ~. We conclude that (p, a t \u2022 0t(=) itf (p, a) \u2022 a(V ). \u2022 If my \"-y \u2022 C: Let (p,a) \u2022 a(m)/\"4. Then (z, ]p,a) \u2022 5c. This implies that there is a state z' reachable with n e-moves (n > 0) from m such that z'f -V' \u2022 C and",
"type_str": "figure",
"num": null
},
"FIGREF8": {
"uris": null,
"text": "Hence, (~, p, ~) \u2022 ~c and (p,.) \u2022 ~(v). Conversely, let (p, a) \u2022 (z(y). Then (11,P, a) \u2022 6c. Front the construction also (z,/, V) \u2022 6c, hence (Iv,,,) \u2022 ,~(=) and (p, a) \u2022 ~,(~.)f~. 263 If x ~ V \u2022 C: The simulation witnessing a(z) ~a a(V) is simply the subset relation. Suppose (p, a) \u2022 a(m). We conclude (z,p, a) \u2022 ~c, but ~o (v, e, =) \u2022 ~c. Hence, (V,P, a) \u2022 ic and (p, a t E a(y).",
"type_str": "figure",
"num": null
},
"FIGREF9": {
"uris": null,
"text": "= e and lt~z \u2022 C: since ot is asolution, there exists a simulation A with cr(y)Aot(z) [= ~(~)~l. 3. p = f and zf -y \u2022 C: A =ID, since ~(=)/a = ~(v).4. p= e and=-s 6 C: A =ID, sincea(zAt O A=)* (the transitive closure of their union), then a(y)Aa(z)q \"4 and a(s)Aa(y)r \"a. But now, since oz(y)r \"4 I and A is a simulation, also cr(y)rAAot(z)qAr \"~.Suppose t) does not hold, but (.,4, c,) ~ C. there is a string zpa \u2022 L(A/'c) such that Case 1: =pb \u2022 L(JV*c) where a # b. Then know with lemma 1 that a \"4 ~A a(m)p.a and bA ~.4 ~x(z)p.4. But this Contradicts condition 1) for a simulation: oz(z)f t = a \"t # b \"4 = ~,(=)p,4. Case 2: zp] 6 L(A/c).",
"type_str": "figure",
"num": null
}
}
}
}