| { |
| "paper_id": "C86-1028", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T13:15:14.289196Z" |
| }, |
| "title": "Lexicase Parsing: A Lexicon-driven App.roach. to Syntactic Analysis", |
| "authors": [ |
| { |
| "first": "Stanley", |
| "middle": [], |
| "last": "Starosta", |
| "suffix": "", |
| "affiliation": { |
| "laboratory": "", |
| "institution": "University of lIawaii Social Science Research Institute and Pacific international Center for lIigh Technology Research Hoaohdu", |
| "location": { |
| "postCode": "96822", |
| "settlement": "Hawaii", |
| "country": "U.S.A" |
| } |
| }, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "This paper presents a lexicon-based approach to syntactic analysis, l,exicase, and applies it to a lexicon driven computatlolml parsing system. The basic descriptive mechanism in a l,exicase grammar is lexieal features. The properties of lexieal items are represented by contextual and non-contextual features, and generalizations are expressed as relationships among sets of these features and among sets of lexieal entries. Syntactic tree strue{,uros are representaed as networks of pairwise dependency relationships among the words in a sentence. Possible dependencies are marked as contextual features on individual lexical items, and Lexicase parsing ix a process of picking out words in a string and attaching dependents to them in accordance with their contextual features. Lexiease is an appropriate vehicle for parsing because I,exicase analyses are monostratal, fiat, and relatively non-abstract, and it is well suited to machine translation because grammatical rel)resentations for corresponding smrtences in two languages will Im very similar to each other in structure and inter-constituent relations, and teas far easier to interconvert.", |
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| "abstract": [ |
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| "text": "This paper presents a lexicon-based approach to syntactic analysis, l,exicase, and applies it to a lexicon driven computatlolml parsing system. The basic descriptive mechanism in a l,exicase grammar is lexieal features. The properties of lexieal items are represented by contextual and non-contextual features, and generalizations are expressed as relationships among sets of these features and among sets of lexieal entries. Syntactic tree strue{,uros are representaed as networks of pairwise dependency relationships among the words in a sentence. Possible dependencies are marked as contextual features on individual lexical items, and Lexicase parsing ix a process of picking out words in a string and attaching dependents to them in accordance with their contextual features. Lexiease is an appropriate vehicle for parsing because I,exicase analyses are monostratal, fiat, and relatively non-abstract, and it is well suited to machine translation because grammatical rel)resentations for corresponding smrtences in two languages will Im very similar to each other in structure and inter-constituent relations, and teas far easier to interconvert.", |
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| "section": "Abstract", |
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| "text": "There are a number of current frameworks of syntactic analysis which have been used as the basis for natural language processing. Many suffer from serious metatheoretical or pra(:tieal defects, especially in the areas of power and descriptive adequacy. Several more recent syntactic fl'ameworks, including I,exical-Functional Grammar [1], Generalized Phrase Structure Grammm\" [2] , and Lexiease [3] have begun to take these problems seriously, and to consider al)plications to natural language processi~g. This paper will be concerned with the application of lexiease grammatical theory to computer parsing of natural language texts.", |
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| "section": "Introduction", |
| "sec_num": "1." |
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| "text": "The point of view which we will adopt here is a very simple one: sentences are hierarchically structured strings of words, and grammar is a statement about the internal composition and external distributions of words. Proceeding from this basis, it is possible to construct a fornml and explicit grannnatical fl'amework of limited generative power which is capable of stating language-specific and universal generalizations in a natural way, unhh}dered by pretheoretieal a priori assumptions about VP's, etc. The fl'amework so constructed, lexiease [13] , [4] , [5] , turns out to have a significant 1)otential for application in the processing of natural language [6] ,", |
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| "start": 549, |
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| "text": "[13]", |
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| "text": "[4]", |
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| "section": "Introduction", |
| "sec_num": "1." |
| }, |
| { |
| "text": "The basic descriptive mechanism in a lexiease grammar is lexieal features.", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Introduction", |
| "sec_num": "1." |
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| "text": "The properties of lexieal items are represented by eantextual and non-.contexttlal features, aud generalizations are expressed as relationships among sets of these features. The ways in which words can combine together are strongly restricted by the Sisterhead Constraint [3] , which states that a word can contract a grammatleal relationship only with the head of a dependent sister eonstruetlon, and tbe One-bar Constraint lop. ell,l, which requires every construction to have at least one lexical head. The result is syntaetie tree representations which are flatter, since there are no intermediate nodes between lexical entries and their maximal projections, and more universal, since there are only a very limited number of ways in which languages can differ in their grammars. These properties turn out to make lexicase especially well suited to machine translation, since the grammatical representations for Hirosato NOMURA NT'T Basic Research Laboratories Musashino.shi, Tokyo, 180, Japan corresponding sentences in two languages will be very similar to each other in structm'e and inter constituent relations, and thus far' easler to intcrconvert.", |
| "cite_spans": [ |
| { |
| "start": 272, |
| "end": 275, |
| "text": "[3]", |
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| "section": "Introduction", |
| "sec_num": "1." |
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| "text": "This paper begins with a briefdescriptiml of the basic structure of a lexieasc grammar, and then describes an algorithm which applies lexlease principles to sentence parsing. Because of space limitations, we will not provide a full explication of the whole theory here. Instead, we will place the primary focus on the ways in whieh particular lexicase principles aid in the straightforward and efficlcnt construction of syntactic tree representations for input sentences. Section 2 describes the way in which grammatical information can be presented as a ~;et of generalizations about classes of lexical items represented in a dependency-type tree format. Section 3 describes tire various types of lexicase feahn'es and their respective roles in a gramamr. Section 4 discusses tim representation of structural infer elation about individual sentences in terms of a tree representation, and sections 5 and 6 present an algorithm showing how the inibrmation provided by a lexicase grammar may be used in parsing.", |
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| "section": "Introduction", |
| "sec_num": "1." |
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| "text": "l,exicase is part of the generative grammar tradition, with its name derived from Chomsky's lexiealist hypothesis [7] and Filhnore's Case (_h'annnar 18]. It has also been strongly influenced by l!',uropean grammatical theory, especially the localistie case grammar and dependency approaches of Jolm Anderson [91 and his recent and classical predecessors. I,ike Chomskyan generative grammar, it is an attempt to provide a psychologically wdid description of tile linguistic competence of a native speaker, but it differs fl'om Chomsky's grammatical fl'amework in power, since it has no transformational rules, and in generativity, since it requires grammatical z'ules and representations to be expressed formally and explicitly and not just talked about. The rules of lexlcase grammm\" proper are lexlcal rules, rules that express relations among lexicaI items and among features within ]exieal entries.", |
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| "ref_spans": [], |
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| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
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| "text": "There are no rules for constructing or modifying trees, and trees are generated by the lexicon rather than by rules: the structural representation of a sentence is aay sequence of words connected by lines in a way which satisfies the contextual features of all the words and does not violate the Sisterhead or Onebar Constraints or the eouventim~s for constructing well-formed trees. A lexiease parsing algorithm, aeeordingly, is just a mechanism for linldng pairs of words together in a dependency relationship which satisfies these contextual features and tree-forming conventions. ([1l] , [12] , and [131 rm. a very similar but independently developed approach which evolved fi'om the computational rather than the linguistic direction.) Figure 1 lists the rule types in a lexiease grammar and their interrelationships. Redundaney rules supply all predictable features to lexieal entries, which are stored in their maximally reduced tbrms, with all predictable features extracted. For example, all pronotms are necessarily members of the class of nouns, and since the feature [ q N] is thus predictable fl'om the [ q prnnl (pronoun) feature, [-I-NI can be omitted from pronoun entries in the lexicon and supplied to the entry by a demon, a lexical Igedtmdan%~ Rule, daring processing.", |
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| "start": 584, |
| "end": 589, |
| "text": "([1l]", |
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| "start": 592, |
| "end": 596, |
| "text": "[12]", |
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| "ref_spans": [ |
| { |
| "start": 741, |
| "end": 749, |
| "text": "Figure 1", |
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| } |
| ], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Subcategorization rules characterize choices that are available within a particular category. These rules are of two subtypes, inflectional and lexicah Fer example, one in[leetioual Suhcategorization Rule states that English count nouns may be marked as either singular or plural. The other type of Subcategorization Rule does not allow an actual choice, but rather characterizes binary subcategories of a lexical categery.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "For example, there is a non-inflectional Subcategorization Rule which states that English non-pronouns are either proper or common.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Inflectional Redundancy Rules state the contextual consequences of a particular choice of inflectional feature. Thus the choice of the feature 'plural' on a head noun triggers the addition of a contextual feature to its matrix stating that none of its dependent sisters may be singular.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Derivation Rules characterize relations between distinct but related lexical entries. For example, they provide a means of associating 'quality' adjectives with corresponding -ly manner adverbs. Due to the non-productivity of ahnost all derivational relations, both derived and underivcd lexical items must be stored and accessed separately in the lexicon, so these rules play only a minor role in parsing. (They are however the major loxicase mechanism for stating the interrelationships of sentence constructions such as active and passive clauses.)", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Phrase-level phonological rules and anaphorie rules are the only non-lexieal rules in the lexicase system. The latter mark pronouns, 'gaps' or qmles', and other anaphorie devices as coreforential or noneoreferential, and so are a very important component of an adequate parsing system, tlowever, a discussion of this question would go well beyond the intended boundaries of this paper.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "With the rules and constraints outlined in this section, it is possible to radically simplify a grammar and the associated lexicon in ways which facilitate parsing, as detailed below.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Rules and representations in Iexiease theory", |
| "sec_num": "2." |
| }, |
| { |
| "text": "As mentioned above, lexical features in a lexiease grammar are of two types: contextual and non-contextual.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Features in lexiease", |
| "sec_num": "3." |
| }, |
| { |
| "text": "Contextual features specify ordering and dependency relationships among major syntactic categories ('parts of speech'), agreement and government requirements, and 'selection', semantic implications imposed by head items on their dependents. The inventory of case relations is as short as it is because lexicase establishes a more efficient division of labor: much of the semantic information formerly carried by case relation differences in Fillmorean-type case ,'elations is now carried by the semantic subcategory features of classes of verbs, and by the semantic features of the case markers themselves.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Features in lexiease", |
| "sec_num": "3." |
| }, |
| { |
| "text": "The resulting reduced nonredundant case relation inventory improves the efficiency of caserelated parsing procedures, and makes it possible to capture significant generalizations about case marking that are not possible with the usual extended inventories used in other case grammar and natural language processing systems. It is necessary to refer to case relations in parsing structures containing multi-argument predicates, in accounting for anaphora and semantic scope phenomena and ~ext coherence, and of course in translation. Again, however, a discussion here of this aspect of lexicase parsing would go beyond the scope of this paper.", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Features in lexiease", |
| "sec_num": "3." |
| }, |
| { |
| "text": "(2) (3ase forms Unlike case relations, syntactic-semantic categories whose presence is inferred indirectly in order to account for lexical derivation and scope and anaphora phenomena, case forms are configurations o\u00a3 surface case markers such as word order, prepositions, postpositlons, case inflections, or relator nouns which function to mark the presence of case relations. They are grouped together into equivalence classes functionally in terms of which case relations they identify, and semantically on the basis of shared localistic features as established by means of componential analysis. Case forms in a lexicase grammar are thus composite rather than atomic. Each is composed of one. or nmre features, either purely gramrnatical ones such as :t2 Nominative (q~ Nom), which characterizes the grammatical subject of a sentence, or localistic ones such as source, goal, terminus, surface, association, etc.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Features in lexiease", |
| "sec_num": "3." |
| }, |
| { |
| "text": "Semantically, case forms carry most of the relational information in a sentence, and are used by the parser in recognizing the presence of particular ease relations. For example, it is necessary to refer to them in for example identifying subjects in order to check for subjectverb agreement. Since so much 'case relation'-type information has been found to be present lexieally in the case markers themselves, they bear much of the semantic load in the semantic analysis of relationships among lexieal items, so that this information need not be duplicated by proliferating parallel ease relations. This means that in parsing, such information is obtainable directly by simply accessing the lexical entries of the case-markers rather than by more cmnplex inference procedures needed to identify the presence of the more usual Filhnore-type case relations.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Features in lexiease", |
| "sec_num": "3." |
| }, |
| { |
| "text": "the perceived central participant in a state or event Agent (AGT):", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Patient (PAT):", |
| "sec_num": null |
| }, |
| { |
| "text": "the perceived external instigator, initiator, controller, or experienccr of the action, event, or state Locus (LOC):", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Patient (PAT):", |
| "sec_num": null |
| }, |
| { |
| "text": "inner: the perceived concrete or abstract source, goal, or location of the Patient outer: the perceived concrete or abstract source, goal, or location of the action,event, or state Correspondent (CAR):", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Patient (PAT):", |
| "sec_num": null |
| }, |
| { |
| "text": "inner: the entity perceived as being in correspondence with the Patient outer: the perceived external frame or point of reference for the action, event, or state as a whole Means (MNS):", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Patient (PAT):", |
| "sec_num": null |
| }, |
| { |
| "text": "inner: the perceived immediate affeetor or effeetor of the Patient outer: the means by which the action, state, or event as a whole is perceived as being realize (", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Patient (PAT):", |
| "sec_num": null |
| }, |
| { |
| "text": "A small inventory of major atomic syntactic category features is assmncd by lexicase, currently limited to the following seven: noun (N), verb (V), adverb (Adv), preposition or postposition (P), sentence particle (SPort), adjective (Adj), and determiner (Det).", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "3) Syntactic category features", |
| "sec_num": null |
| }, |
| { |
| "text": "syntactic categories are divided into syntactic subcatego,'ies based on differences in distribution. Thus nouns are divided into pronouns (no modifiers allowed), proper nouns (no adjectives and typically no determiners allowed), mass nouns (not pluralizable), etc., and similarly for the other syntactic classes. The contextual features associated with the words in these various distributional classes determine which words are dependent on which other words, and thus are very important in assigning correct b'ees to parsed sentences. Lexicase assumes that there must be enough semantic featm'es marked on lexical items so that every lexieal item is differentiated from every other (non-synonymous) item by at least one distinctive semantic feature. These features are not directly involved in parsing, but may figure in the identification of metaphors in sentences which do not have any other well-formed parsings. Contextual features may refer to dependents occm'ring on the left or on the right, or they may be non directional, referring to sister dependents on either' side when the presence of some category is important but the order varies (as in topicalization and Fmglish subject-auxiliary inversion) or is irrelevant (as in fl'ce word-order languages). Although the violation of a selectional feature does not result in ungrammatlcality, solectionaI features are usefal in parsing to pick the most promising branch in parsing a sentence when two or more diffm'ent links are possible for a given word, or in identifying metaphors when no well-formed parse of a sentence is otherwise possible.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Major", |
| "sec_num": null |
| }, |
| { |
| "text": "Since the 'range' of contextual features is sharply lhnited by the Sisterhead Constraint, only certain kir~ds of links between words are possible, and only those words directly connected by a single link need be checked for the satisfaction ef grammatical requirements such as case fl'ames, agreement featm'es, etc. This greatly limits the number of places a parser has to cheek in determining the well-formedness of a given sentence, and so facilitates parsing.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Major", |
| "sec_num": null |
| }, |
| { |
| "text": "Contextual fcatm'es may be positive, negative or optional. Positive contextual features state the presence of a required dependent, and are used in parsing to establish initial links between pairs of words. Negative features klentify classes of words which are not allowed to occur as dependent sisters, and serve in parsing to reject some of the links nmde in accordance with positive features. Optional featm'es do not require or reject any links, but rather serve to keep open tire possiblity of linking pairs of words by a general procedure applying near the end of the algoritt~m (see 6.3 below). All links which are not marked as permissible in this way are ruled out by the 'Omega Rule', a lexical Redundancy Rule which states the defimlt value for tire 'linkabillty' of given pairs of wm'ds: all liukings which are not explicitly allowed for are disallowed.", |
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| "section": "Major", |
| "sec_num": null |
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| "text": "The most iml)ortant charactm'istic for all contextual features for the purposes of parsing is tile Sisterhcad Constraint: in (lctenninh~g whether a contextual feature is satisfied for a given item, the parser need look only at the head words of its sister eategm'ies.", |
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| "ref_spans": [], |
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| "section": "Major", |
| "sec_num": null |
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| "text": "In lexicase, tree diagrams arc graphic representations of dependency and constituency relationships holding among pairs of words in a sentence, and thus indirectly of relations among the constructions of which these words are the heads. Two types of constructions are recognized: endocentric and exoeentrle. These two construction types can be identified and their internal and external dependency relations determined directly from the kinds of lines by which they are connected in a Iexiease tree representation (or, equlwdently, by their bracketing in a LISP-type parenthesis notation): i) vertical lines link a phrasal node with its head: a unitlength line indicates a lexical head, and a two-unit-length line identifies a phrasal head of an exoeentrie construction; it) slanting lines link an endoeentrie phrasal node with its dependents; and iii) horizontal lines link the vertical lines above the lexieal or phrasal heads of an cxocentrie construction.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "An endoeentrie construction is any syntactic construction which has only one obligatory member, i.e. one head, which in accordance with the lexiease One-Bar Constraint must be a single lexicai item. nouns and verbs respectively. In a tree, the head word of an endocentric construction has a vertical line of unit-length above it.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "An exoccntric construction on the other hand has more than one obligatory constituent. Again, the One-Bar Constraint requires that at least one of the constituents must be a single word, the lexical head of the construction. The other obligatory head (or heads) may be a word or a phrase.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "Examples of exocentric constructions are prepositional phrases and coordinate constructions. In a tree, each of the co-heads of an exocentric construction has a vertical line above it, of unit-length above lexical co-heads and two-unit-length above the lexical heads of phrasal co-heads. The apexes of the vertical lines are joined by a horizontal line, in effect an elongated node. Examples of both types of phrases appear in Figure 3 .", |
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| "start": 427, |
| "end": 435, |
| "text": "Figure 3", |
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| ], |
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| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "The gramatically relevant relationships between pairs of nodes in a tree are expressed in lexicase in terms of the notions 'command' and 'cap-command' (from Latin caput, capitis 'head'): i) a wm'd cap-commands the lexlcal heads of its dependent sisters; thus in the two trees in Figure 3 , a) 'boy' cap-commands 'that', 'on', and 'bus', since 'boy' has two dependent sister constituents (indicated by slanting lines), 'that' and 'on the bus there'. The lexical head of the construction 'that' (stlown by a vertical line) is the word 'that'. However 'on the bus there' is an exocentric construction (shown by a horizontal llne) which has two heads (shown by vertical lines), 'on' and 'the bus there'. The lexical head of 'on' is 'on', and the lexical head of 'the bus there (vertical line) is 'bus'. b) 'on' cap-commands 'bus', since 'on' has a single dependent sister (the phrasal co&cad of the exocentric construction 'on the bus there'), 'the bus there', and the lexical head of 'the bus there' is 'bus'. Finally, c) 'bus' cap-commands 'the' and 'there', since 'bus' has two dependent sisters, 'the' mad 'there', and the respective heads of these two constructions are the words 'the' and 'there'.", |
| "cite_spans": [], |
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| { |
| "start": 279, |
| "end": 287, |
| "text": "Figure 3", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "ii) a word X commands a word Y if elther a) X cap-commands Y, or b) X cap-commands Z and Z commands Y.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "Thus for example 'boy' commands 'there' because 'boy' capcommands 'bus' and 'bus' cap-connnands 'there'; however 'that' does not command 'there' because 'that' has no dependent sisters at all, and so does not cap-command anything.", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "The notion 'cap-command' plays a crucial role in defining the domain of subcategorization. To determine which constituents are relevant in subcategorization, lexicase appeals to the Sisterhead Constraint, which maintains that 'contextual features are marked on the lexical heads of constructions, and refer only to lexlcal heads of sister constructions' [3]. That is, a word is subcategorized only by the words which it cap-commands.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "For example, a verb may be subcategorized by the heads of the noun phrases which are its sisters, but not by the other constituents which are inside the NP's. Conversely, a noun may not be subcategorized by any constituent outside the NP. However, in the case of exocentric constructions such as prepositional phrases, the head words of botl~'all obligatory cohead constituents are accessible for subcategorization, since they are all cap-commanded by the higher head item.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "To illustrate, in the Noun Phrase in Figm'e 3 (a) , the lexical head of the construction is the noun 'boy'. Following the Sisterhead Constraint, the contextual features marked on 'boy' can refer only to features of the words it cap-commands, in this case 'that' and the heads of the exocentric PP, 'on' and 'bus', but not to 'the' or 'there'. The features of both the preposition and the head of its sister NP fall within the domain of subcategorization of the cap-commanding lexical item and jointly subcategorize it. Their features taken together are said to form a 'virtual matrix', i.e. a matrix which is not the lexical specification of any single lexical item, but which is rather a composite of the (non-contextual) features of all of the lexical heads of the construction [3]. In the lexicase parsing algorithm discussed in this paper, the effect of a virtual matrix has been achieved by copying the features of the phrasal head (the lexical head of the phrasal co-. head, e.g. 'bus' in 'on the bus') into the matrix of the lexicaI head (e.g. 'on' in 'on the bus' in Figure 3) . The matrix of the preposition 'on' then becomes in effect the virtual matrix of the exocentric construction, representing the grammatically significant features for the whole PP. There are a number of other constraints in lexiease which apply to syntactic trees [3] . The effect of these constraints is to limit the class of possible trees and, consequently, the class of possible analyses. One constraint is that all terminal nodes are words, not morphemes or empty categories. A related constraint states that syntactic features are marked only on lexieal items, not on nodes or on ad hoe abstract lexieal categories. Finally, lexicase requires that every construction have at least one immediate lexieal head; that is, there can be no intervening non-Iexical node between the phrasal node and the lcxlcal head of the phrase. In X-bar terminology, lexiease allows phrasal nodes with a maxinmm of one bar, where an S is equivalent to V-bar.", |
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| "start": 1349, |
| "end": 1352, |
| "text": "[3]", |
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| ], |
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| { |
| "start": 37, |
| "end": 49, |
| "text": "Figm'e 3 (a)", |
| "ref_id": null |
| }, |
| { |
| "start": 1075, |
| "end": 1084, |
| "text": "Figure 3)", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "The interaction of the tree-drawing conventions, the One-bar limitation, and the Sisterhead Constraint makes it possible to eliminate both phrasal and major category labels from syntactic trees without any loss of information [3] . The matrix of an individual lexieal item contains information about its syntactic category, making a category node label redundant.", |
| "cite_spans": [ |
| { |
| "start": 226, |
| "end": 229, |
| "text": "[3]", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "With the One-Bar Constraint, the nature of the phrasal construction can be determined with reference to tbe lexieal category of the head of the construction, which is identifiable by the unit-length vertical line above it. Thus any node directly attached to a lower [+N] item by a vertical line of unit-length is an NP, so it is redundant to mark such a node by the label 'NP'. As a consequence, the tree representatiml in Figure 5 which has no node labels overtly marked is adequate for the representation of all constituency and dependency information. Note that the CCJN ('conjunction-bar') 'my Dad and Rufus' in Figure 5 is still an NP in function, because a coordinate construction is exocentric, and so the virtual matrix associated with 'my Dad and Rufus' contains the feature [+N] as well as [+cejnl, making it an NP for external subcategorizing purposes.", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 423, |
| "end": 431, |
| "text": "Figure 5", |
| "ref_id": null |
| }, |
| { |
| "start": 616, |
| "end": 624, |
| "text": "Figure 5", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "The single-level lexicase tree notation incorporates the information carried by the three different kinds of tree structure contrasted by Winograd [10], dependency (head and modifier), phrase structure (immediate constituents), and role structure (slot and filler). Because it allows no VP constituent, it can equate constituent structure with dependency structure. The case role of a constituent is the case role of its lexical head. Thus semantic information is readily extracted from the syntactic representation, because the representation links together those words which are semantically as well as syntactically related. Figure 6 shows the fundamental components of the Iexiease parser. The function of these components in brief is as follows:", |
| "cite_spans": [], |
| "ref_spans": [ |
| { |
| "start": 628, |
| "end": 636, |
| "text": "Figure 6", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "Lexiease tree representation", |
| "sec_num": "4." |
| }, |
| { |
| "text": "(1) Pre-proeessor This procedure replaces the word forms in the input sentence by hmnographic fully specified lexicaI entries, that is, entries with identical spelling, specified for all contextual and non-contextual syntactic features as well as contextual and non contextual semantic features ('selection'd restrictions'). If an input form matches more than one lexical entry, replace the form by a 'cluster', a list of all the lcxical entries whose forms match tim input form. The output is a string composed of lexieal entries and clusters of lexical entries which is isomorphous with the input string of word forms.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The parsing algorithm", |
| "sec_num": "5." |
| }, |
| { |
| "text": "(2) Morphological analyzer If an input fin'm is not matched by any item listed in the lexicon, the morphological analyzer checks to see if the form matches any stored stem-affix pattern. If it does, the form is divided into stem plus inflectional affix and the stem is markcd with the syntactic class features associated with tile pattern.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The parsing algorithm", |
| "sec_num": "5." |
| }, |
| { |
| "text": "Using inflectional Subcategorization Rules, the stem is expanded into its full inflectional paradigm, and the original input word form is replaced by a 'cluster' composed of those (ffdly ,~;pecifled) members of tile inflectional paradigm which are homographic with the original word lbrm.", |
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| "ref_spans": [], |
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| "section": "The parsing algorithm", |
| "sec_num": "5." |
| }, |
| { |
| "text": "(3) l'laeeholder substitution Each cluster of homographic lexical entries in the substitution string is temporarily replaced by a 'placeholder' entry composed of the intersection of the form and features of all the entries in tile cluster. If the entries have nothing in common hut the form itself, then the placeholder will be the form alone, with no associated feature matrix.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The parsing algorithm", |
| "sec_num": "5." |
| }, |
| { |
| "text": "If the lcxical entries in a cluster have enough featnres ill con'nnon to be equivalent in terms of linldag potential, they are linked into the tree structure as a group during the parsing process. When the structures containing clusters of entries are subsequently resolved into lexically unambiguous structures during placeholder expansion, many of the necessary links will have ah'eady been nmde, and will net have to be repeated for each separate but syntactically equivalent homographic enlry.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "The parsing algorithm", |
| "sec_num": "5." |
| }, |
| { |
| "text": "Each substitution string containing plaeeholder clusters is expanded into separate structm'es by replacing the clusters with subclustcrs of items sharing nlore features in comn'lon, and ultimately with their original constituent hldividual entries. After each cluster is resolved into subclusters or individual entries, the resultant substitution strings are passed through the parser again to add links that become possible as the new clusters and entries become accessible.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "As with the previous parsing phase, this phase establishes links that work for clusters of honmgraphie items, so that these links do not have to be nmde separately and repeatedly for each substitution string containing a different homographic item. In this way, no sequence of words ever has to be rcparsed.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "(5) Parser", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "Based on the positive contextual syntactic features of head lexical items, the beads are linked to eligible and accessible dependent items. As each link is established, the negative contextual \u00a3eatm'es are checked. If there is a violation, that track is immediately abandoned. Note that exactly the same negative contextual feature mechanism takes carc of two distinct contextual dependency phenomena: i) general cooccurrencc properties, such as the fact that English nouns may not have following Determiners, and ii) grammatical agreement; thus for example subjce.t-verb agreement is stated as a negative contextual feature: a finite verb marked for plural nlay not have a dependent Nominative sister marked singular. (Ar.tually the matter is somewhat more complex than this, but a fidl discussion would go beyond the scope of this paper.)", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "After each pair of words has been linked in accordance with positive and negative grammatical contextual features, implicational semantic contextual features C,;eleetienal restrictions') are checked for compatibility. If a violation is found, that string is semantically allonlalous.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "Lexicase theory is designed such that only the heads of sister categories need to be considered in determining whether there is an inconsistency in a structure being parsed. That is, only words directly connected by a single line need to be checked for the satisfaction or violation of any grammatical or selectional contextual requirement, and this checking can be done immediately afte.r each link is first made. If a violation is found, the structure can be shunted off on a siding immediately without wasting time examining surrounding material. The parsing procedm'e will be considered in somewhat more detail in the section 6.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(d) Plaeeholder expansion", |
| "sec_num": null |
| }, |
| { |
| "text": "The outptlt of tile algorithm is zero or nmre syntactic analyses of the input sentcnce, but at the same time it can be considered an intensional semantic representation: it presents all the sernantic distinctive features for each word, and specifies the head-modifier and semantic implication relations between each linked pair of wm'ds. The 'extensional' meaning of the sentence then is just tile range of external situations which are compatible with the intension, the lexical meanings and interrelationships characterized by this structure.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(6) Output", |
| "sec_num": null |
| }, |
| { |
| "text": "I,exicase is very well suited to characterizing this intcasional semantic representation bccausc it formally defines the range of possible loxical linkages. The structure is simple yet rich enough to in principle carry enough information to serve as the input to a know]edge extraction or machine translation system.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(6) Output", |
| "sec_num": null |
| }, |
| { |
| "text": "(1) Prepositions:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "IAnk each preposition by contextual features with an accessible N, V, or P. Prepositions are linked first because they link with N's, V's, or other P's to form PP's wbich delimit closed domains whose internal non-head constituents are then inaccessible to connections with external elements. Subsequent parsing stages then search inside of or outside of these dmnains, but do not need to consider links between PP-internal not>heads and PPexternal lexical items.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "(2) Verbs:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "Verbs are linked with their attributes to form clauses or sentences. Note that in the lexicase framework, 'sentence' refers to any verb-headed construction, regardless of the finiteness of its verbal head or its position in the tree. The searching proceedes from left to right in English, but would scan fi'om right to left in a verb-final left-branching language such as Japanese.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "In a dependency grammar framework such as lexicase, a (verbal) sentence is defined as a verb together with its syntactic dependents. A sentence is the basic unit of syntax because it is the maximum domain of dependencies. Once a sentence unit has been established in this way, subsequent parsing stages can ignore links between sentence-internal and sentence-external items.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "(3)Nouns:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "Nouns are linked with their dependents to form Noun Phrases. Noun Phrases and Sentences ('verb phrases') are the syntactically and semantically basic sentence constituents. Like other head items, nouns establish domains whose non-head constituents are inaccessible to external links, so that cross-domain Iinkages can be ignored on subsequent passes, thereby radically limiting the number of pairs of items that have to be considered on each subsequent pass and again cutting down on computation time.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "(4) Determiners:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "Link each Determiner with an accessible Noun. In English, the Determiner marks the left boundary of a Noun Phrase. Linking the N and its Det establishes one boundary of the NP, and subsequent parsing can ignore links between elements inside this domain and elements outside it.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Words", |
| "sec_num": "6.1" |
| }, |
| { |
| "text": "Link each Adjective with an adjacent noun. Because previous passes will have already delimited major constituent boundaries and radically narrowed the set of possible connections, very little checking will need to be done to link an Adjective with the correct head Noun.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(5) Adjectives", |
| "sec_num": null |
| }, |
| { |
| "text": "Link each Adverb with a head Verb or Adjective. Structural ambiguity is most likely to appear in connection with alternate attachments of PP's and Adverbs with other words in a sentence. By saving Adverb linking until near the end of the parsing sequence, we establish domains of inaccessibility which greatly reduce the number of possible Adverb attachment points which need to be considered.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "(6) Adverbs:", |
| "sec_num": null |
| }, |
| { |
| "text": "Link each conjunction with one or more major constituents (S, NP, PP, AdjP, or AdvP) on each side. At this point, all the major constituents have already been established, so the conjunction linking procedure needs to consider only the head word of each major constituent. Since every conjunction will at this time be either at the highest level, that is, linkable only to the immediate constituents of the sentence, or inside the domain of some other construction, thc number of linking choices will be extremely limited.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Coordination", |
| "sec_num": "6.2" |
| }, |
| { |
| "text": "Link all remaining upwardly unlinked Nouns, Determiners, Adjectives, Adverbs, Prepositions, and Verbs with an accessible 'elder sister' (or 'regent' [12] ). At this point unattached lexical items will be found only embedded inside of other constructions, with very few accessible attachment possibilities to consider (usually only one). Thus there will generally be no backtracking and stacking required. The exception will be Adverbs and PP's, which account for most of the structural ambiguity likely to be encountered. By saving these alternative connection possiblities until near the end of the parsing process, we minimize the amount of computation that has to be done 'on top of' the alternative structures produced at this stage.", |
| "cite_spans": [ |
| { |
| "start": 149, |
| "end": 153, |
| "text": "[12]", |
| "ref_id": "BIBREF9" |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Orphanage", |
| "sec_num": "6.3" |
| }, |
| { |
| "text": "The parsing approach we advocate here is in principle very simple because lexicase requires no rules for normal parsing situations at all, and is based on linguistic principles designed to maximize the generality and simplicity of descriptions. It has no deep structure or 132 transformations; instead, 'transformed' and 'untransformed' lexical entries are listed separately in the lexicon, thereby placing the parsing burden on memory rather than processing. Since Iexicase automatically determines which items are relevant to the satisfaction of particular contextual requirements, no feature percolation or feature copying mechanism is needed to move features around in a tree to get them into a position where they are accessible to related items.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Overall assessment and conclusion", |
| "sec_num": "7." |
| }, |
| { |
| "text": "Lexicase parsing is bottom-up in the sense that it begins with individual words rather than some 'root node' S. It scans from left to right or vice versa, depending on whether the language is verbinitial, verb-medial, or verb-final, but in fact it is a mechanism which works from head to dependent rather than primarily from one end or the other. Since it forms constituents from heads and dependents at all levels simultaneously, it thus incorporates virtues of both topdown and bottom-up parsers. Lexicase accomplishes this by only making links allowed or required by contextual features of head lexical items, and since the 'overall structure of the sentence' is determined by just these features, it is not possible to make links which are not compatible with this overall structure.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Overall assessment and conclusion", |
| "sec_num": "7." |
| }, |
| { |
| "text": "Since lexicase has no Phrase Structure rules, a lexicase parser cannot blunder into the loops caused by left-recursive rules. Lexicase generates linguistically correct structures: they directly represent head-attribute relationships, they characterize the concept of grammatical relatedness, they allow various other important generalizations to be captured, and they account adequately for speakers' intuitions.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Overall assessment and conclusion", |
| "sec_num": "7." |
| } |
| ], |
| "back_matter": [], |
| "bib_entries": { |
| "BIBREF0": { |
| "ref_id": "b0", |
| "title": "Lexical-Functional Grammar: A Formal System for Grammatical Representation", |
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| "FIGREF0": { |
| "text": "Case relations in lexicase", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF1": { |
| "text": "Inflectional features Traditional inflectional categories such as person, number, gender, case, tense, etc., are b'eated in lexicase as fl-eely variable features which are not stored in their lexical entries (except in the cases of unpredictable forms), but are rather added as needed by a Subeategorizatien Rule in the course of processing. Inflection is typically involved in agreement, and agreement relationships (in conjm~ction with the Sisterhood Constrahrt) are important in locating and linking together those words bearing a head dependent relationship to each other. (5) Semantic features", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF2": { |
| "text": "Selcetional features are also contextual, but they differ in function from grammatical contextual features. Thus a verb like the there my (a) Noun phrase (b) Sentence Fig. 3 l,exicase tree representations 'love' may impose an animate interpretation on its subject by means of the following selcctional feature: [D[+AGT, -anmt]].", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF3": { |
| "text": "The other constituents of such constructions are phrases which are syntactically optional dependents of the head word. Noun Phrases and Sentences for example arc endocentric constructions, headed by ,, JJa(| lit iI.lS c ........ ] [ ES\",~;,] E\"-',,','~ my Fig. 4 The domain of the verb 'saw' C+~cni m,r., L'\" g ] [-+?AT] ] F ..... 1 my L ~ N j L ~. N j E * l)a ] \u00a2cnj = coordinating conjunction Fig. 5 Tree representation with category features", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF4": { |
| "text": "Sisterhead Constraint makes it possible to define the notion of syntactic domain as all those constituents whose heads are referred to by the contextual features of a particular lexieal item. For example, the domain of the verb 'saw' in the example of Figure 3 is indicated in Figure 4 with ease relations. Thus the domain of the verb 'saw' in this sentence consists of the arguments marked [ + PAT] and [+AGT]. The determiner 'my', on the other hand, is not in the domain of the verb; rather, it is in the dmnain of its own dominating lloon~ 'Dad'.", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "FIGREF5": { |
| "text": "Fig. 6 Fundanmntalcomponentsofthelexicaseparser", |
| "uris": null, |
| "type_str": "figure", |
| "num": null |
| }, |
| "TABREF1": { |
| "text": "English nouns states that English determiners may not follow their nouns; another feature, [+[+I)et]], is marked on definite common nouns to show that they must reoccur with determiners, and a third, [-[-plrl]], marks plural nouns as not allowing non-plural attributes. The feature [+([+Adj])] on common nouns states that they may have adjectival attributes, a possibility which would otherwise be excluded by the Omega-rule (see below).", |
| "html": null, |
| "num": null, |
| "content": "<table><tr><td colspan=\"3\">(6) Contextual features</td></tr><tr><td colspan=\"3\">Contextual features are the part of the lexical representation</td></tr><tr><td colspan=\"3\">which makes phrase structure rules unnecessary.</td><td>A contextual</td></tr><tr><td colspan=\"3\">feature is a Idnd of atmnic valence, stating which other words may</td></tr><tr><td colspan=\"3\">attach to a giwm word as dependents to form the molecules called</td></tr><tr><td colspan=\"2\">'sentences'.</td><td>Contextual features may function syntactically,</td></tr><tr><td colspan=\"3\">morphologically, or semantieally.</td><td>For example, tile feature</td></tr><tr><td>[-[-F</td><td colspan=\"2\">Det]] on</td></tr></table>", |
| "type_str": "table" |
| } |
| } |
| } |
| } |
