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<Paper uid="P82-1009">
  <Title>THEORETICAL/TECHNICAL ISSUES IN NATURAL LANGUAGE ACCESS TO DATABASES</Title>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
AGGREGATE FUNCTIONS AND QUANTITY QUESTIONS
</SectionTitle>
    <Paragraph position="0"> Questions such as &amp;quot;How many employees are in the sales department?&amp;quot; must be mapped into three radically different database query language expressions depending on how the database is set up. It may he appropriate to retrieve a pre-stored total number of employees from a NUMBER-OF-EMPLOYEES field of a DEPARTMENT file, or to count the number of records in an EMPLOYEE file that have the value SALES in the DEPARTMENT field, or, if departments are broken down into offices with which are associated the total numbers of employees employed therein, to total the values of the NUMBER-OF-EMPLOYEES field in all the records for offices in the sales department.</Paragraph>
    <Paragraph position="1"> In the TQA System there are a number of different levels of representation of a given query. The grammar which assigns structure to a query has some core components which are essentially application-independent (e.g., the cyclic and postcyclic transformations) and has other components that are application-dependent (e.g., portions of the lexicon and precyclic transformations). Surface structures are mapped by the application-independent post cyclic and cyclic transformations into a relatively deep structural level which is referred to as the underlying structure level. In this representation, sentence nodes are expanded into a verb followed by a sequence of noun phrases, and the representation of reference is facilitated by the use of logical variables XI, X2, .... The underlying structure corresponding to the previously cited example sentence would be something like the following (suppressing details):</Paragraph>
  </Section>
  <Section position="3" start_page="0" end_page="51" type="metho">
    <SectionTitle>
LOCATED WH SOME MANY EMPLOYEE X1 SALES DEPARTMENT
</SectionTitle>
    <Paragraph position="0"> Now, depending on feature information associated with the lexical items in the two NP's, application-specific precyclic transformations can be formulated to map this underlying structure into any of three query structures that directly reflect the three data structures and corresponding formal queries previously discussed. Rather than sketching query structures that could be produced for this example, let me be more specific by substituting the actual treatment of two similar sentences currently treated by the TQA System land-use application.</Paragraph>
    <Paragraph position="1"> These are the sentences:  (i) &amp;quot;How many parking lots are there in ward 1 block 2?&amp;quot; (2) &amp;quot;How many parking spaces are there in ward 1 block 2?&amp;quot;  In the current data base, individual lots are identified as being parking lots by a land use code relation LUCF, which has attributes that include JACCN (parcel account number) and LUC (land use code). Parking lots have an LUC value of 460. Another relation, PARCFL, has attributes which include JACCN and JPRK (the number of parking spaces on a given parcel).</Paragraph>
    <Paragraph position="2"> The underlying structures assigned to both these sentences are nearly identical, differing only in the lexical distinctions between &amp;quot;parking lot&amp;quot; and &amp;quot;parking space&amp;quot;. The common structure is very much like that of the previously given tree structure except that PARKING LOT or PARKING SPACE (together with their associated features) replaces EMPLOYEE,  uisites) triggers a pair of precyclic transformations. The action of those two transformations is roughly indicated by the following sequence of bracketted terminal strings (the actual trees together with all their features would take up much more space):</Paragraph>
    <Paragraph position="4"> Note that the lot ~nsertion transformation LOTINS2 has produced structure of the type which is more directly assigned to the input query, &amp;quot;What is the total number of parking spaces in the lots which are located in ward 1 block 2?&amp;quot;. This structure is then further transformed by a transformation LOCATION that replaces the abstract verb LOCATED by a verb (WBLOCK in this instance) which corresponds to an existing data base relation.</Paragraph>
  </Section>
  <Section position="4" start_page="51" end_page="51" type="metho">
    <SectionTitle>
LOCATION
</SectionTitle>
    <Paragraph position="0"/>
    <Paragraph position="2"> The latter structure is mapped via the TQA Knuth attribute grammar formalism into the logical form:</Paragraph>
    <Paragraph position="4"> This logical form is in a set domain logical calculus to be discussed later in the paper. Roughly, it denotes the set of elements X46 such that X46 is the sum of the members of the bag (like a set, but with possible duplicate elements) of elements X3 such that a certain set is not empty, namely the set of elements X48 such that X48 is the account number (JACCN) of a parcel whose number of parking spaces (JPRK) is X3 and whose wardblock (WBLOCK) is 100200.</Paragraph>
    <Paragraph position="5"> The expression</Paragraph>
  </Section>
  <Section position="5" start_page="51" end_page="51" type="metho">
    <SectionTitle>
(RELATION 'PARCFL
</SectionTitle>
    <Paragraph position="0"/>
    <Paragraph position="2"> in the above logical form denotes the proposition that the relation formed from the PARCFL relation by projecting over the attributes JPRK and JACCN contains the tuple (X3 X48). The logical form is straightforwardly translated by means of a LISP program whose details we will not concern ourselves with into the SQL query:</Paragraph>
  </Section>
  <Section position="6" start_page="51" end_page="52" type="metho">
    <SectionTitle>
SELECT SUM(A.JPRK)
FROM PARCFL A
WHERE A.WBLOCK = '100200';
</SectionTitle>
    <Paragraph position="0"> The other structure (for the sentence with PARKING LOT) lacks the triggering feature + UNIT, and hence .transformations TOTPUNIT and LOTINS2 do not apply; furthermore, the LOCATION transformation applies to the original instance of the verb LOCATED rather than the copy of LOCATED introduced by the lot insertion transformation LOTINS2 in the analysis of the previous sentence:</Paragraph>
    <Paragraph position="2"> This structure is mapped via the Knuth attribute grammar into the logical form:</Paragraph>
    <Paragraph position="4"> and this logical form is translated to the SQL query:</Paragraph>
  </Section>
  <Section position="7" start_page="52" end_page="52" type="metho">
    <SectionTitle>
SELECT COUNT(UNIQUEA.JACCN)
</SectionTitle>
    <Paragraph position="0"> FROM PARCFL A, LUCF B WHERE AoJACCN = B.JACCN AND BdegLUC = '0460' AND A.WBLOCK = '100200' ; ~qle points to be made with respect to this  treatment are that the information indicating differential, database-specific treatment can be encoded in lexical features, and that differential treatment itself can be implemented by means of precyclic transformations which are formally of the same type that the TQA system uses to relate underlying to surface structures. The features, such as + UNIT in our example, are principled enough to permit their specification by a data base administrator with the help of an on-line application customization program. (+ UNIT is also required in lexical items such as DWELLING UNITS and STORIES).</Paragraph>
    <Paragraph position="1"> If the database organization had been different, simple lexical changes could have been made to trigger different sequences of transformations, resulting in structures and ultimately SQL expressions appropriate for that database organization. In this way, it would be easy to handle such database organizations as that in which the total number of parking lots and/or parking spaces is stored for each wardblock, and that in which such totals are stored for each splitblock which is included within a given wardblock.</Paragraph>
  </Section>
  <Section position="8" start_page="52" end_page="52" type="metho">
    <SectionTitle>
QUERYING SE~IANTICALLY COMPLEX FIELDS
</SectionTitle>
    <Paragraph position="0"> In posing this problem, the session chairman pointed out that natural language query systems usually assume that the Concepts represented by data-base fields will always be expressed in English by single words or fixed phrases. He cited as an example the query &amp;quot;Is John Jones a child of an alumnus?&amp;quot; where &amp;quot;child of an alumnus&amp;quot; is a fixed phrase expressing the binary relation with attributes APPLICANT (whose values are the names of applicants) and CHILD-0F-ALUMNUS (whose values are either T or F). He further noted that related queries such as &amp;quot;Is one of John Jones' parents an alumnus?&amp;quot; or &amp;quot;Did either parent of John Jones attend the college?)&amp;quot; require some different treatment.</Paragraph>
    <Paragraph position="1"> The approach we have taken in TQA is, insofar as possible, to provide the necessary coverage to permit all the locutions that are natural in a given application. The formalism by which this is attempted is, once again, the transformational apparatus. Transformations often coalesce queries which have the same meaning but differ substantially in their surface forms into common underlying or query structures. There is~ however, no requirement that this always be done, so such queries are sometimes mapped into logically equivalent rather than identical query structures. In either case, the transformational formalism provides a solid basis for assigning very deep semantic structures to a wide spectrum of surface sentence structures. The extent to which we have been successful in allowing broad coverage of logically equivalent alternative statements of a query is difficult to quantify, but we believe that we have done well relative to other efforts for two reasons: (I) We have made an effort to cover as many underlying relations and their surface realizations as possible in treating a given application, and (2) The transformational formalism we use is effective in providing the broa~ coverage which reflects all the allowable interactions between the syntactic phenomena treated by a particular grammar.</Paragraph>
  </Section>
  <Section position="9" start_page="52" end_page="53" type="metho">
    <SectionTitle>
MULTI-FILE QUERIES
</SectionTitle>
    <Paragraph position="0"> This problem deals with multi-file databases and the questions of which files are relevant to a given query and how they should be joined. This &amp;quot;problem&amp;quot; is one which is often raised, and which invariably reflects a quick-and-dirty approach to syntactic and semantic analysis. Within a framework such as that provided by the transformational apparatus in TQA, this problem simply doesn't arise. More accurately, it is a problem which doesn't arise if an adequate grammar is produced that assigns structure of the depth of the TQA System's query structures. This, of course, is no easy task, but it is one which is central to the transformational grammar-based approach~ and its successful treatment does provide a principled basis for eliminating a number of potential difficulties such as this multi-file query problem.</Paragraph>
    <Paragraph position="1"> To see why this is so, let us consider how, for a given query, relations are identified and joined in TQA. As we have already indicated, TQA underlying structures and query structures consist of sentence nodes which dominate a verb followed by a sequence of noun phrases. These simple structures are joined together to form a complete sentence structure through the use of additional phrase structure rules which indicate conjunction, relative clause-main clause connection, etc. Query structure verbs correspond, for the most part, to database relations, and the noun phrase arguments of those verbs correspond to attributes of their a~sociated relations. Furthermore, query structures contain logical variables which serve the function of establishing reference, including identity of reference. Thus if the query structure assigned to a query identifies two (or more) relations which have attributes whose values are the same logical variable, we have an indication that it is those attributes over which the relations should be joined.</Paragraph>
    <Paragraph position="2"> An example should make this clearer. Consider the query structure which TQA assigns to the sentence null &amp;quot;What is the zone of the vacant parcels in subplanning area 410?&amp;quot;  (We omit feature information and some structure which is irrelevant to the subsequent discussion in the structure below.)</Paragraph>
    <Paragraph position="4"> This structure represents the set of elements X4 such that X4 is the zone of an element of the set of lots X8 such that the land use code (LUC) of X8 is 910 and the subplanning area (SUBPLAN_AREA) of X8 is 410. The structure is mapped in straightforward fashion by a Knuth attribute grammar translation procedure into the set domain relational calculus expression:</Paragraph>
    <Paragraph position="6"> Each deep (query structure) verb such as ZONE has associated with it (by means of a translation table entry) a relation, which is usually the projection of an existing data base relation. Thus instead of translating a portion of the above tree to (ZONE X4 X8), an expression which is true if X4 is the zone of the parcel whose account number is XS, the translation table is used to produce</Paragraph>
  </Section>
  <Section position="10" start_page="53" end_page="53" type="metho">
    <SectionTitle>
(RELATION 'ZONEF
</SectionTitle>
    <Paragraph position="0"/>
    <Paragraph position="2"> which is true if the projection of the ZONEF relation over attributes ZONE and JACCN (account number) contains a tuple (X4 XS).</Paragraph>
    <Paragraph position="3"> The conjunction of three relations with a common JACCN attribute value of X8 indicates that the three relations are to be joined over the attribute JACC ~' There is, however, one complication in translating the relatiorul calculus expression above into a formal query language such as SQL. The relations ZONEF and LUCF are existing database relations, but there is no relation GEOBASE* in the database, giving the subplanning area of specific parcels.</Paragraph>
    <Paragraph position="4"> Instead, the PARCEL relation gives the splitblock (SBLOCK) of a given parcel (JACCN) and the GEOBASE relation gives the subplanning area (SUBPLA) of all the parcels within a given splitblock (SBLOCK).</Paragraph>
    <Paragraph position="5"> There are at least three solutions to the problem of bridging the gap between relational calculus expressions such as this and appropriate formal query language expressions. These are: (i) Write a precyclic database-specific splitblock insertion transformation which assigns query structure corresponding to the query, &amp;quot;What are the zones of the vacant parcels which are located in splitblocks in subplanning area 410?&amp;quot; (2) Store information that permits replacing expressions involving virtual relations such as  sible for providing a formal query language definition of the virtual relations produced. In this case that would take the form of defining GEOBASE* as the appropriate join of projections over GEOBASE and PARCFL.</Paragraph>
    <Paragraph position="6"> All three solutions have been implemented in the TQA System and used in specific cases as seems appropriate. For a database system with the definitional facilities available in SQL, solution (3) is particularly attractive because it is the type of activity with which data base administrators are familiar. Solutions (I) and (2) were also implemented at various times for examples such as the one in question, leading to the following SQL query:</Paragraph>
  </Section>
  <Section position="11" start_page="53" end_page="54" type="metho">
    <SectionTitle>
SELECT UNIQUE A.ZONE, A.JACCN
FROM ZONEF A, GEOBASE B, PARCFL C, LUCF D
WHERE A.JACCN = C.JACCN
AND C.JACCN = D.JACCN
AND B.SBLOCK = C.SBLOCK
AND D.LUC = '0910'
AND B.SUBPLA= '4100';
</SectionTitle>
    <Paragraph position="0"> (We note for the careful reader that '0910' and '4100' are not misprints, but the discussion of how such normalization can be automatically achieved from DBA declarations is outside the scope of the present paper.)</Paragraph>
  </Section>
  <Section position="12" start_page="54" end_page="54" type="metho">
    <SectionTitle>
TRANSLATING QUANTIFIED RELATIONAL CALCULUS
EXPRESSIONS TO FORMAL QUERY LANGUAGE EQUIVALENTS
</SectionTitle>
    <Paragraph position="0"> In this section we consider a problem of our own choosing. In most of the existing relational calculus formalisms, use is made of logical variables and some type of universal and existential quantifiers.</Paragraph>
    <Paragraph position="1"> Early versions of TQA were typical in this respect.</Paragraph>
    <Paragraph position="2"> The version of TQA which was tested in the White Plains experiment, for example, made use of quantifiefs FORATLEAST and FORALL whose nature is best explained by an example. The lozical form assigned to the previously considered sentence was, at one time:  of parcels X8 which are in subplanning area 410 and have a land use code of 910, parcel XII2 is in zone X4. In simple examples such as this, where only existential quantification of logical forms is involved, there is no problem in translating to a formal query language such as SQL. However, when various combinations of existential and universal quantification are involved in a logical form, the corresponding quantification-indicating constructs to be used in the formal query language translation of that logical form is not at all obvious. An examination of the literature indicates that the arguments used in establishing the completeness of query languages offer little or no guidance as to the construction of a practical translator from relational calculus to a formal query language such as SQL. Hence, the approach used in translating TQA logical forms to corresponding SQL expressions will be discussed, in the expectation of eliciting explanations of how the translation of quantification is handled in other systems.</Paragraph>
    <Paragraph position="3"> We begin by observing that a logical form (foratleast 1Xl (setx X2 (f X2)) (g El)) (which denotes the proposition that for at least one Xl which belongs to the set of elements X2 such that f(X2) is true, g(Xl) is true) is equivalent to the requirement of the non-emptiness of the set (I) (setx 'Xl '(@nd (f Xl) (g XI))) Similarly,</Paragraph>
    <Paragraph position="5"> (which denotes the proposition that for all X1 in the set of elements X2 such that f(X2) is true, g(Xl) is true), is equivalent to a requirement of the emptiness of the set (2) (setx 'XI '(and (f Xl) (not (g Xl)))) Conversion of expressions with universal and existential quantifiers is then possible to expressions involving only set notation and a predicate involving the emptiness of a set. The latter type of expressions are called set domain relational calculus expressions.</Paragraph>
    <Paragraph position="6"> Fortunately, SQL provides operators EXISTS and NOT EXISTS which take as their argument an SQL SELECT expression, the type of expression into which logical forms of the type (setx 'XI ... ) are translated. A recursive call to the basic logical form-to-SQL translation facility then suffices to supply the SQL argument of EXISTS or NOT EXISTS.</Paragraph>
    <Paragraph position="7"> It is worth noting that, under certain circumstances which we will not explore here, the &amp;quot;(setx X2&amp;quot; portion of an embedded expression (setx 'X2 (f X2)) can be pulled forward, creating a prefix-normal-form-like expression of the type (setx 'Xl (setx 'X2 ... )), and the logical variables that can be pulled all the way forward correspond to information implicitly requested in English queries.</Paragraph>
    <Paragraph position="8"> The values which satisfy these variables should also be printed to satisfy users' implicit requests for information. For example, in our previously considered query &amp;quot;What are the zones of the vacant parcels in subplanning area 410?&amp;quot; one probably wants the parcels identified in addition to their zones. Translation to the form of set domain relational calculus used in TQA then provides a basis for either taking the initiative in automatically printing these implicitly requested values or for engaging in a dialog with the user to determine whether they should be printed.</Paragraph>
    <Paragraph position="9"> As a final example of this method of translating quantified logical forms, consider the sentence &amp;quot;What gas stations are in a ward in which there is no drug store?&amp;quot; The logical form initially assigned by TQA to this</Paragraph>
  </Section>
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