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<Paper uid="P86-1010">
  <Title>PARSING A FREE-WORD ORDER LANGUAGE: WARLPIRI</Title>
  <Section position="4" start_page="0" end_page="0" type="metho">
    <SectionTitle>
A SAMPLE SENTENCE
</SectionTitle>
    <Paragraph position="0"> In order to make the presentation of the parser a little less abstract, a sample sentence of Warlpiri is shown in (1):  (1) Ngajulu-rlu ka-rna-rla punta-rni kurdu-ku karli. I-ERG PRES-1-3 take-NPST child-DAT boomerang  'I am taking the boomerang from the child.' (The hyphens are introduced for the nonspeaker of Warlpiri in order to clearly delimit the morphemes.) The second word, karnarla, is the auxiliary which must appear in the second (Wackernagel's) position. Except for the auxiliary, the other words may be uttered in any order; there are 4! ways of saying this sentence.</Paragraph>
    <Paragraph position="1"> The parser assumes that the input sentence can l~e broken into its constituent words and morphemes. ~ Sentence (1) would be represented as in (2). The parser can not yet handle the auxiliary, so it has been omitted from the input.</Paragraph>
  </Section>
  <Section position="5" start_page="0" end_page="61" type="metho">
    <SectionTitle>
((NGAJULU RLU) (PUNTA RNI) (KURDU KU) (KARLI))
ARGUMENT IDENTIFICATION
</SectionTitle>
    <Paragraph position="0"> Before presenting the lexicon, GB argument identification as it is construed for the parser is presented? Case is used to identify syntactic arguments and to link them to their syntactic predicates {e.g., verbal, nominal and infinitival). There are three such cases in Warlpiri: ergative, absolutive and dative.</Paragraph>
    <Paragraph position="1"> Argument identification is effected by four subsystems involving case: selection, case-marking, case-assignment, and argument-linking. Only maximal projections (e.g., NP and VP, in English) are eligible to be arguments. In order ~Barton (1985) has written a morphological analyzer that breaks down Warlpiri words in their constituent morphemes. We have connected both parsers so that the user is able to enter sentences in a less stilted form. Input (2), however, is given directly to the main parser, bypassing Barton's analyzer.</Paragraph>
    <Paragraph position="2"> ZThis analysis of Warlpiri comes from several sources, and from the helpful assistance of Mary Laughren. See, for example, (Laughren, 1978; Nash, 1980; Hale, 1983).</Paragraph>
    <Paragraph position="4"> The actions for performing argument identification~ as well as the data on which they operate, are stored for each lexical item in the lexicon* The part of the lexicon necessary to parse sentence (2) is given in figure 2.</Paragraph>
    <Paragraph position="5"> The lexicon is intended to be a transparent encoding  for such a category to be identified as an argument, it must be visible to each of the four subsystems. That is, it must qualify to be selected by a case-marker, marked for its case, assigned its ease, and then linked to an argument slot demanding that case.</Paragraph>
    <Paragraph position="6"> Selection is a directed action that, for Warlpiri, may take the category preceding it as its object. This follows from the setting of the head parameter of GB: Warlpiri is a head-final language* Selection involves a co-projection of the selector and its object, where both categories are projected one level* For example, the tensed element, rni, selects verbs, and then co-projects to form the combined &amp;quot;inflected verb&amp;quot; category* An example is presented below* The other three events occur under the undirected structural relation of siblinghood. That is, the active category (e.g., case-marker) must be a sibling of the passive category (e.g., category being marked for the case).</Paragraph>
    <Paragraph position="7"> Consider figure 1. The dative case-marker, ku, selects its preceding sibling, kurdu, for dative case. Once co-projected, the dative case-marker may then mark its selected sibling for dative case. Because ku is also a caseassigner, and because kurdu has already been marked for dative case, it may also be assigned dative case. The projected category may then be linked to dative case by punta-rni which links dative arguments to the source thematic (0) role because it has been assigned dative case. In this example, the dative case-marker performed the first three actions of argument identification, and the verb performed the last. Note that only when kurdu was selected for case was precedence information used; case-marking, case-assignment and argument-linking are not directional.</Paragraph>
    <Paragraph position="8"> In this way, the fixed-morpheme order and free-word order have been properly accounted for.</Paragraph>
    <Paragraph position="9">  of the linguistic knowledge. CONJUGATION stands for the conjugation class of the verb; in Warlpiri there are five conjugation classes. SELECT takes a list of two arguments.</Paragraph>
    <Paragraph position="10"> The first is the element that will denote selection; in the case of a grammatical case-marker, it is the grammatical case. The second argument is the list of data that the prospective object must match in order to be selected. For example, rlu requires that its object be a noun in order to be selected.</Paragraph>
    <Paragraph position="11"> The representation for a lexicon is simply a list of morpheme-value pairs; lookup consists simply of searching for the morpheme in the lexicon and returning the value associated with it. The associated value consists of the information that is stored within a category, namely, data and actions. Only the information that is lexically determined, such as person and number for pronouns, is stored in the lexicon.</Paragraph>
    <Paragraph position="12"> There is another class of lexical information, lexical rules, which applies across categories. For example, all verbs in Warlpiri with an agent 0-role assign ergative case. Since this case-assignment is a feature of all verbs, it would not be appropriate to store the action in each verbal entry; instead, it stated once as a rule. These rules are represented straightforwardly as a list of pattern-action pairs. After lexical look-up is performed, the list of rules is applied. If the pattern of the rule matches the category, the rule fires, i.e., the information specified in the &amp;quot;action&amp;quot; part of the rule is added to the category. For an example, see the parse of the inflected verb, puntarni, in figure 4, below.</Paragraph>
  </Section>
  <Section position="6" start_page="61" end_page="61" type="metho">
    <SectionTitle>
THE BASIC DATA STRUCTURES
</SectionTitle>
    <Paragraph position="0"> The basic data structure of the parsing engine is the projection, which is represented as a tree of categories.</Paragraph>
    <Paragraph position="1"> Both dominance and precedence information is recorded explicitly. It should be noted, however, that the precedence relations are not considered in all of the processing; they are taken into account only when they are needed, i.e., when a category is being selected.</Paragraph>
    <Paragraph position="2"> While the phrase-marker is being constructed there may be several independent projections that have not yet been connected, as, for example, when two arguments have preceded their predicate. For this reason, the phrase-marker is represented as a forest, specifically with an array of pointers to the roots of the independent projections. An array is used in lieu of a set because the precedence information is needed sometimes, i.e., when selecting a category, as above.</Paragraph>
    <Paragraph position="3"> These two structures contain all of the necessary structural relations for parsing. However, in the interests of explicit representation and speeding up the parser somewhat, two auxiliary structures are employed. The argument set points to all of the categories in the phrase-marker that may serve as arguments to predicates. Only maximal projections may be entered in this set, in keeping with Xtheory. Note that a maximal projection may serve as an argument of more than one predi(:ate, so that a category is never removed from the argument set.</Paragraph>
    <Paragraph position="4"> The second auxiliary structure is the set of unsatisfied predicates, which points to all of the categories in the phrase-marker that have unexecuted actions. Unlike the argument set, when the actions of a predicate are executed, the category is removed from the set.</Paragraph>
    <Paragraph position="5"> The phrase-marker contains all of the structural relations required by GB; however, there is much more information that must be represented in the output of the parser. This information is stored in the feature-value lists associated with each category. There are two kinds of features: data and actions. There may be any number of data and actions, as dictated by GB; that is, the representation does not constrain the data and actions. The actions of a category are found by performing a look-up in its feature-value list. On the other hand, the data for a category are found by collecting the data for itself and each of the sub-categories in its projection in a recursive manner. This is done because data are not percolated up projections.</Paragraph>
    <Paragraph position="6"> The list of actions is not completely determined. Selection, case-marking, case-assignment, and argument linking are represented as actions (el. the discussion of case, above). It should be noted that these are the only actions available to the lexicon writer. Actions do not consist of arbitrary code that may be executed, such as when an arc is traversed in an ATN system. The supplied actions, as derived from GB, should provide a comprehensive set of linguistically relevant operations needed to parse any sentence of the target language.</Paragraph>
    <Paragraph position="7"> Although the list of data types is not yet complete, a few have already proved necessary, such as person and number information for nominal categories. The list of 0roles for which a predicate subcategorizes is also stored as data for the category.</Paragraph>
  </Section>
  <Section position="7" start_page="61" end_page="61" type="metho">
    <SectionTitle>
THE PARSING ENGINE
</SectionTitle>
    <Paragraph position="0"> The parsing engine is the core of both the lexical and the syntactic parsers. Therefore, their operations can be described at the same time. The syntactic parser is just the parsing engine that accepts sentences (i.e., lists of words) as input, and returns syntactic phrase-markers as output.</Paragraph>
    <Paragraph position="1"> The lexical parser is just the parsing engine that accepts words (i.e., lists of morphemes) as input, and returns lexical phrase-markers as output.</Paragraph>
    <Paragraph position="2"> The engine loops through each component of the input, performing two computations. First it calls its subordinate parser (e.g., the lexical parser is the subordinate parser of the syntactic parser) to parse the component, yielding a phrase-marker. (The subordinate parser for the lexical parser performs a look-up of the morpheme in the lexicon.) In the second computation, the set of unsatisfied predicates is traversed to see if any of the predicates' actions can  apply. This is where selection, case-marking, projection, and so on, are performed.</Paragraph>
    <Paragraph position="3"> Note that there is no possible ambiguity during the identification of arguments with their predicates. This stems from the fact that selection may only apply to the (single) category preceding the predicate category, and that each of the subsequent actions may only apply serially. This assumes single-noun noun phrases. In the next version of the parser, multiple-noun noun phrases will be tackled. However, the addition of word stress information will serve to disambiguate noun grouping.</Paragraph>
    <Paragraph position="4"> There may be ambiguity in the parsing of the morphemes. That is, there may be more than one entry for a single morpheme. The details of this disambiguation are not clear. One possible solution is to split the parsing process into one process for each entry, and to let each daughter process continue on its own. This solution, however, is rather brute-force and does not take advantage of the limited ambiguity of multiple lexical entries. For the moment, the parser will assume that only unambiguous morphemes are given to it.</Paragraph>
    <Paragraph position="5"> After the loop is complete, the engine performs default actions. One example is the selection for and marking of absolutive case. In Warlpiri, the absolutive case-marker is not phonologically overt. The absolutive case-marker is left as a default, where, if a noun has not been marked for a case upon completion of lexical parsing, absolutive case is marked. This is how karli is parsed in sentence (2); see figures 6 and 7, below.</Paragraph>
    <Paragraph position="6"> The next operation of the engine is to check the well-formedness of the parse. For both the lexical parser and the syntactic parser, one condition is that the phrase-marker consist of a single tree, i.e., that all constituents have been linked into a single structure. This condition subsumes the Case Filter of GB. In order for a noun phrase to be linked to its predicate it must have received case; any noun phrase that has not received case will not be linked to the projection of the predicate, and the phrase-marker will not consist of a single tree.</Paragraph>
    <Paragraph position="7"> The last operation percolates unexecuted actions to the root of the phrase-marker, for use at the next higher level of parsing. For example, the assignment of both ergative case and absolutive case in the verb puntarni are not executed at the lexical level of parsing. So, the actions are percolated to the root of the phrase-marker for the conjugated verb, and are available for syntactic parsing. In the parse of sentence (2), they are, in fact, executed at the syntactic level.</Paragraph>
  </Section>
  <Section position="8" start_page="61" end_page="63" type="metho">
    <SectionTitle>
TWO PARSED WORDS
</SectionTitle>
    <Paragraph position="0"> The parse of kurduku, meaning 'child' marked for dative case, is presented in figure 3. It consists of a phrase-marker with a single root, corresponding to the declined noun. It has two children, one of which is the noun, kurdu, and the other the case-marker, ku.</Paragraph>
    <Paragraph position="1"> O: actions: ASSIGN: DATIVE  One can see that all three actions of the case-marker have executed. The selection caused the noun, kurdu, and the case-marker, ku, to co-project; furthermore, the noun was marked as selected (SELECT: DATIVE appears in its data). Marking and assignment also are evident. Note that all three actions percolated up the projection. This is due to the PERCOLATE: T datum for ku, which forces the actions to percolate instead of simply being deleted upon execution. The actions of case-markers percolate because they can be used in complex noun phrase formation, marking nouns that precede them at the syntactic level.</Paragraph>
    <Paragraph position="2"> This phenomenon has not yet been fully implemented. The TIME datum is used simply to record the order in which the morphemes appeared in the input so that the precedence information may be retained in the parse. One more note: the PROJECTION? field is true when the category's parent is a member of its projection, and false when it isn't. Because the top-level category in the phrase-marker is a projection of both subordinate categories, the PRO-JECTION? entries for both of them are true.</Paragraph>
    <Paragraph position="3"> In figure 4, the parse of puntarni is shown. There is much more information here than was present for each of the lexical entries for the verb, punta, and the tensed element, rni. The added information comes from the application of lexical rules, mentioned above. These rules first associate the 8-roles with their corresponding cases, as can be seen in the data entry for punta. Second,&amp;quot; they set up the INTERNAL and EXTERNAL actions which project one and two levels, respectively, in syntax. That is, the agent, which will be marked with ergative case, will fill the subject position; the theme and the source, which will be marked with absolutive and dative cases, will fill the object positions. null  O: actions: ASSIGN: ABSOLUTIVE</Paragraph>
  </Section>
  <Section position="9" start_page="63" end_page="63" type="metho">
    <SectionTitle>
A PARSED SENTENCE
</SectionTitle>
    <Paragraph position="0"> The phrase-marker for sentence (2) is given in figure 5.</Paragraph>
    <Paragraph position="1"> The corresponding parse for this sentence is shown in figures 6 and 7, the actual output of the parser. In the parse, the verb has projected two levels, as per its projection actions, INTERNAL and EXTERNAL. These two actions are particular to the syntactic parser, which is why they were not executed at the lexical level when they were introduced. INTERNAL causes the verb to project one level, and inserts the LINK action for the object cases. EXTERNAL causes a second level of projection, and inserts the LINK action for the subject case. Note that the TIME information is now stored at the level of lexical projections; these are the times when the lexical projections were presented to the syntactic parser.</Paragraph>
    <Paragraph position="2"> To demonstrate the parser's ability to correctly parse free word order sentences, the other 23 permutations of sentence (2) were given to the parser. The phrase-markers constructed, omitted here for the sake of brevity, were equivalent to the phrase-marker above. That is, except for the ordering of the constituents, the domination relations were the same: the noun marked for ergative case was in all cases the subject, associated with the agent 8-role; and the nouns marked for absolutive and dative cases were in all cases the objects, associated with the theme and source 8-roles, respectively.</Paragraph>
    <Paragraph position="3"> punta- rni kurdukarli null ku</Paragraph>
  </Section>
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