{ "paper_id": "P80-1030", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T08:43:05.660754Z" }, "title": "PHRAN -A Knowledge-Based Nature] Language Understender", "authors": [ { "first": "Robert", "middle": [], "last": "Wilensky", "suffix": "", "affiliation": { "laboratory": "", "institution": "University of California at Berkeley", "location": {} }, "email": "" }, { "first": "Yigal", "middle": [], "last": "Arena", "suffix": "", "affiliation": { "laboratory": "", "institution": "University of California at Berkeley", "location": {} }, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "We have developed an approach to natural language processing in which the natural language processor is viewed as a knowledge-based system whose knowledge is about the meanings of the utterances of its language. The approach is orzented around the phrase rather than the word as the basic unit. We believe that this paradi~ for language processing not only extends the capabilities of other natural language systems, but handles those tasks that previous systems could perform in e more systematic and extensible manner. We have construqted a natural language analysis program called PHRAN (PHRasal ANalyzer) based in this approach. This model has a number of advantages over existing systems, including the ability to understand a wider variety of language utterances, increased processlng speed in some cases, a clear separation of control structure from data structure, a knowledge base that could be shared by a language productxon mechanism, greater ease of extensibility, and the ability to store some useful forms of knowledge that cannot readily be added to other systems.", "pdf_parse": { "paper_id": "P80-1030", "_pdf_hash": "", "abstract": [ { "text": "We have developed an approach to natural language processing in which the natural language processor is viewed as a knowledge-based system whose knowledge is about the meanings of the utterances of its language. The approach is orzented around the phrase rather than the word as the basic unit. We believe that this paradi~ for language processing not only extends the capabilities of other natural language systems, but handles those tasks that previous systems could perform in e more systematic and extensible manner. We have construqted a natural language analysis program called PHRAN (PHRasal ANalyzer) based in this approach. This model has a number of advantages over existing systems, including the ability to understand a wider variety of language utterances, increased processlng speed in some cases, a clear separation of control structure from data structure, a knowledge base that could be shared by a language productxon mechanism, greater ease of extensibility, and the ability to store some useful forms of knowledge that cannot readily be added to other systems.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "The problem of constructing a natural language ~rocessing system may be viewed as a problem oz constructing a knowledge-based system.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "From this orientation, the questions to ask are the following:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "What sort of knowledge does a system need about a language in order to understand the meaning of an utterance or to produce an utterance in that language? How can this knowledge about one's language best be represented, organized and utilized? Can these tasks be achieved so that the resulting system is easy to add to and modify? Moreover, can the system be made to emulate a human language user?", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "Existing natural language processing systems vary considerably in the kinds of knowledge about language they possess, as well as in how thxs knowledge is represented, organized and utilized. However, most of these systems are based on ideas about language that do not come to grips with the fact that a natural, language processor neeos a great deal of knowledge aoout the meaning of its language's utterances.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "Part of the problem is that most current natural language systems assume that the meaning of a natural language utterance can be computed as a function of the constituents of the utterance. The basic constituents of utterances are assumed to be words, and all the knowledge the system has about ~he semantics of its language zs stored at the word level (~i~nbaum etal, 1979) (Riesbeck et al, 1975) (Wilks, 197~) (Woods, 1970) . However, many natural language utterances have interpretations that cannot be found by examining their components. Idioms, canned phrases, lexical collocations, and structural formulas are instances of large classes of language utterances whose interpretation require knowledge about She entire phrase independent of its individual words (Becker, 19q5) (Mitchell, 19~71) .", "cite_spans": [ { "start": 353, "end": 374, "text": "(~i~nbaum etal, 1979)", "ref_id": null }, { "start": 375, "end": 397, "text": "(Riesbeck et al, 1975)", "ref_id": "BIBREF8" }, { "start": 398, "end": 405, "text": "(Wilks,", "ref_id": null }, { "start": 406, "end": 411, "text": "197~)", "ref_id": null }, { "start": 412, "end": 425, "text": "(Woods, 1970)", "ref_id": "BIBREF13" }, { "start": 766, "end": 774, "text": "(Becker,", "ref_id": null }, { "start": 775, "end": 780, "text": "19q5)", "ref_id": null }, { "start": 781, "end": 791, "text": "(Mitchell,", "ref_id": null }, { "start": 792, "end": 798, "text": "19~71)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "We propose as an alternative a model of language use that comes from viewing language processing systems as knowledge-based systems tha\u00a3require the representation and organization of large amounts of knowledge about what the utterances of a language mean. This model has the following properties:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "I. It has knowledge about the meaning of the words of the language, but in addition, much of the system's knowledge is about the meaning of larger forms of u~terancas.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "2. This knowledge is stored in the form of pattern-concept pairs.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "A pattern is a phrasal cons~ruc~ oI varyxng degrees of specificity.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "A concept is a notation that represents the meaning of the phrase.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "Together, this pair associates different forms of utterances with their meanings.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "3. The knowledge about language contained in the system is kept separate from the processing strategies that apply this knowledge to the understanding and production tasks.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "4. The understanding component matches incoming utterances against known patterns, and then uses the concepts associated with the matched patterns to represent the utterance's meaning.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "INTRODUCTION", "sec_num": "1.0" }, { "text": "lookxng for concepts in the caza oase ~net match the concept it wishes to express. The phrasal patterns associated with these concepts are used to generate the natural language utterance.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The production component expresses itself b[", "sec_num": "5." }, { "text": "6. The data-base of pattern-concept pairs is shared by both the unaerstanding mechanism and the mechanism of language production.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The production component expresses itself b[", "sec_num": "5." }, { "text": "Other associations besides meanings may be kept along with a phrase. For example, a description of the contexts in which the phrase is an appropriate way to express its meaning may be stored. A erson or situation strongly associated wi~h the phrase may also be tied to it.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "7.", "sec_num": null }, { "text": "ANalyzer) is a natural language understanding system based on this view of language use. PNNAN reads English text and produces structures that represent its meaning. As it reads an utterance, PHRAN searches its knowledge base of pattern-conceptpairs for patterns that best interpret the text.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "PHRAN CPHRasal", "sec_num": null }, { "text": "The concept portion of these pairs is then used to produce the meaning representation for the utterance.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "PHRAN CPHRasal", "sec_num": null }, { "text": "PHRAN has a number of advantages over previous systems: I. The system is able to handle phrasal language units that are awkwardly handled by previous systems but which are found with great frequency in ordinary speech and common natural language texts.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "PHRAN CPHRasal", "sec_num": null }, { "text": "2. It is simpler to add new information to the system because control and representation are kept separate. To extend the system, new pattern-concept pairs are simply added to the data-base.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "PHRAN CPHRasal", "sec_num": null }, { "text": "and is in principle sharable by a system for language productioD (Such a mechanism is n~w under construction). Thus adding xnxorma~lon ~o the base should extend the capabz]ities of both mechanisms.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The knowledge base used by PHRAN is declarative,", "sec_num": "3." }, { "text": "4. Because associations other than meanings can be stored along with phrasal unzts, the identification of a phrase can provide contextual clues not otherwise available to subsequent processing mechanisms. 5. The model seems to more adequately reflect the psychological reality of human language use.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The knowledge base used by PHRAN is declarative,", "sec_num": "3." }, { "text": "By the term \"phrasal language constructs\" we refer to those language units of which the language user has s~ecific knowledge. We cannot present our entire classification oF these constructs here. However, our phrasal constructs range greatly in flexibility. For example, fixed expressions like \"by and large , the Big Apple (meaning N.Y.C.), and lexical collocations such as \"eye dro~per\" and \"weak safety\" allow little or no modificatxonA idioms like \"kick the bucket\" and \"bury the hatchet allow the verb in them to s~pear in various forms-discontinuous dependencies like look ... up\" permi~ varying positional relationships of their constituents. All these constructs are phrasal in that the language user must know the meaning of the construct as a whole In order to use it correctly.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "In the most general case, a phrase may express the usage of a word sense. For example, to express one usage of the verb kick, the phrase \" \" is used.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "This denotes a person followed by some verb form inyolving kick (e.g., kick, kicked, would ~ave kicked\") followe~\"~ some utterance ueno~ing an oojec~.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "Our notion of a phrasal language construct is similar to a structural formula (Fillmore, 1979 )-However, our criterion for dlr~trl'F/~ing whether a set of forms should be accomodated by the same phrasal pattern is essentially a conceptual one.", "cite_spans": [ { "start": 78, "end": 93, "text": "(Fillmore, 1979", "ref_id": "BIBREF3" } ], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "Since each phrasal pattern in PHRAN is associated with a concept, if the msenlngs of phrases are different, they should be matched by different patterns. If the surface structure of the phrases is similar and they seem to mean the same thing, %hen they should be accomodated by one pattern. At the center of PHRAN is a knowledge base of phrasal patterns.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "These include literal strings such as \"so's your old man\"; patterns such as \" restaurant\", and very ~eneral phrases such as \" .", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "Associated with each phrasal pattern is a conceptual template.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "A conceptual template is a piece of meanln~ representation with possible references to pieces of the associated phrasal pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "For example, associated with the phrasal pattern \" restaurant\" is the conceptual template denoting a restaurant that serves type food; associated with the phrasal pattern \" \" is the conceptual template that denotes a transfer of possession by of to from . ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "pHRASAL LANGUAGE CONSTRUCTS", "sec_num": "2.0" }, { "text": "A pattern-concept pair consists of a specification of the phrasal unit, an associated concept, and some additional information about how the two are related. When PHRAN instantiates a concept, it creates an item called a term that includes the concept as well as some additional information.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Overview Of PHRAN Patterns -", "sec_num": "4.1.2" }, { "text": "A pattern is a sequence of conditions that must hold true for a sequence of terms.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Overview Of PHRAN Patterns -", "sec_num": "4.1.2" }, { "text": "A pattern may specify optional terms toq, the place where these may appear, ana what effect (if any) their appearance will have on the properties of the term formea if the pattern is matched. For example, consider the following informal description of one of the patterns suggested by the mention of the verb 'to eat' in certain contexts. Notice that the third term is marked as optional.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Overview Of PHRAN Patterns -", "sec_num": "4.1.2" }, { "text": "If it is not present in the text, PHRAN will fill'the OBJECT slot with a default representing generic food.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Overview Of PHRAN Patterns -", "sec_num": "4.1.2" }, { "text": "The following is a highly simplified example of how PHRAN processes the sentence \"John dropped out of school\": First the word \"John\" is read. \"John\" matches the patter~ consisting of the literal \"John\", and the concept associated with this pattern causes a term to be formed that represents a noun phrase and a particular male erson named John.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "No other patterns were suggested. ~his term is added on to *CONCEPTS, the list of terms PHRAN keeps and which will eventually contain the meaning of the sentence.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "Thus This new fact is now stored under the last term.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "Next the word \"out\" is read. The pattern suggestion mechanism is alerted by the occurence of the verb 'drop' followed by the word 'out', and at this point It instructs PHRAN to consi ;r the pattern I [ \"out\" \"of\" I [ ... ] !", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The list in *CONCEPT* is checked against this pattern to see if it matches its first two terms, end since that is the case, this fact is stored under the secord term. A term associated with 'out' is now added to *CONCEPT*:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "< [JOHNI -person, NP] , [DROP -verb] , lOUT ] >", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The two patterns that have matched up to DROP are checked to see if the new term extends them. This is true only for the second pattern, a~d this fact is stored unde~ the next term.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The pattern l ) is discarded. Now the word \"of\" is read.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "A term is formed and added to *CONCEPT*.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The pattern that matched to OUT is extended by OF so %he pattern is moved to ~e next term.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The word \"high\" is read and a term is formed and added to *CONCEPt. Now the pattern under OF is compared against HIGH.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "It doesn't satisfy the next condition. PHRAN reads \"school\", and the pattern suggestion routine presents PHRAN with two patterns: The two patterns are compared against the last term, and both are matched. The last two terms a~'e removed from *CONCEPT*, and the patterns under 0F are checked to determine which of the two possible meanings we have should be chosen. Patterns are suggested such that the more specific ones appear first, so that the more specific interpretation will be chosen if all patterns match equally well.. 0nly if the second meanin~ (i.e. a school that is high) were explicitly specifled by a previous pattern, would it have been chosen.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "I. I [ \"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "A term is formed and added to *CONCEPT*, which now contains < [JOHNI -person, NP~ . [DROP -verb] [OUT] , [0FI , [HIGH-SCHOOLI -school, NPJ >", "cite_spans": [ { "start": 62, "end": 96, "text": "[JOHNI -person, NP~ . [DROP -verb]", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The pattern under OF is checked against the last term in *CONCEPT ~.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "PHRAN finds a complete match, so all the matched terms are removed and replaced by the concept associated with this pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "*CONCEPT* now contains this concept as the final result:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "< [ ($SCHOOLING (STUDENT JOHNI) . (SCHOOL HIGH-SCHOOLI) (TERMINATION PREMATURE)) ] > 4.2 Pattern-Concept Pairs In More Detail d.2.1 The Pattern -", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "The pattern portion of a pattern-concept pair consists of a sequence of predicates. These may take one of several forms:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.1.. ~ Simple Example -", "sec_num": null }, { "text": "which will match only a term representing this exact word.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "2. A class name (in parentheses); will match any term ~epresenting a member @f this class (e.g. \"(FOOD)\" or \"(PHYSICAL-OBJECT)\").", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "~. A pair, the first element of which is a property name end the second is a value; will match any ~e rm hav%ng the required valge of the property e.g. \"(Part-0f-Speech VERB)\").", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "In addition, we may negate a condition or specify that a conjunction or disjunction of several must hold.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "The following is one of the patterns which may be suggested by the occurrence of the verb 'give' in an utterance:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "[(PERSON) (BOOT GIVE) (PERSON) (PNYSOB)I 4.2.1.1", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "Optional Parts -To indicate the presence of optional terms, a list of pattern concept-pairs is inserted into the pattern at the appropriate place. These pairs have as their first element a sub-pattern that will match the optional terms. The second part describes how the new term to be formed if the maxo pattern is found should be modified to reflect the existence of the optional sub-pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "The concept corresponding to the optional part of a pattern zs treated in a form slightly different from the way we treat regular concept parts of pattern-concept pairs.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "As usual, it consists of pairs of expressions. The first of each pair will be places as is at ~he end of the properties o~ the term to be formed, end the second will be evaluated first and then placed on that list.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "For example, another pattern suggested when 'give' is seen is the following:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "[(PERSON) (ROOT ~VE).~PHYSOB) (~[T0 (PERSON)) (TO (OPT-VAL 2 CD-FORM))])]", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "The terms of this pattern describe a person, the verb give, and then some pnysical object. The last term describes the optional terms, consisting of the word to followed by a person description. Associated with th~ pattern is a concept part that specifies what to do with the optional part if it is there. Here it specifies that the second term in the optional pattern should fill in the TO slot in the conceptualization associated with the whole pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "This particular pattern need not be a separate pattern in PHRAN from the one that looks for the verb followed by the recipient followed by the object transferred. We often show patterns without all the alternatives that are possible for expositional purposes.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "Sometimes it is simpler to write the actual patterns separately, although we attach no theoretical significance to thxs disposition.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "A word;", "sec_num": null }, { "text": "When a pattern is matched. PHRAN removes the terms that match zt from *CONCEPT* and replaces them with a new term, as defined by the second part of the pattern-concept pair. For example, here is a pattern-concept pazr that may be suggested when the verb \"eat' is encountered: The concept portion of this pair describes a term covering an entire sentence, and whose ~eaning is the action of INGESTing some food (Schank, 1975) . The next two descriptors specify how $o fill in vaTiable parts of this action. The expression (VALUE n prop) specifies the 'prop' property of the n'th term in the matched sequence of the pattern (not including optional terms).", "cite_spans": [ { "start": 410, "end": 424, "text": "(Schank, 1975)", "ref_id": "BIBREF10" } ], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "OFT-VAL does the same thing with regards to a matched optional sub-pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "Thus the concept description above specifies that the actor of the action is to be the term matching the first condition. The object eaten will be either the default concept food, or, if the optional sub-pattern was found, the term corresponding to this suo-pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "Sometimes a slot in the conceptualization can be filled by a term in a higher level pattern of which this one is an element. For example, when analyzing \"John wanted to eat a cupcake\" a slight modification of the previous pattern is used to find the meaning of \"to eat a cupcake\".", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "Since no subject appears In this form, the higher level pattern specifies where it may find it. That is, a pattern associated with \"want\" looks like the following:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "{ ~ ]", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "The Concept -", "sec_num": "4.2.2" }, { "text": "This specifies that the subject of the clause following want is the same as the subject of went.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": ",infinitive DFOHM", "sec_num": null }, { "text": "When s word is read PHRAN compares the ~atterns offered by the pattern suggestin\u00a2 routine with the list *CONCEPT* in ~ne manner aescrioea in ~ne example in section 4.1.3. It discards patterns that confllct with *CONCEPT* and retains the rest. Then FH~AN tries to determine which meaning ?f the word to choose, using the \"active\" patterns (those that have matched up to the point where PHRAN has read). It checks if there is a particular meaning that will match the next slot in some pattern or if no such definition exists if there is a meanin\u00a2 that might be the beginning of a' sequence of terms -whose meaning, as determined via a pa~tern-concept pair, will satisfy the next slot in one of the active patterns.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~.I Reading A Word -", "sec_num": null }, { "text": "If this is the case, that meanin~ of the word is chosen. Otherwise PHRAR defaults to the fzrst of the meanings of the word.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~.I Reading A Word -", "sec_num": null }, { "text": "A new term is formed and if it satisfies the next condition in one of these patterns, the appropriate ~atzsrn Is moved to the pattern-list of the new term. If zhe next condition in the pattern indicates that the term speczfled is optional, %hen PHRAN checks for these Optlonal terms, and if it is convinced that they are not present, it checks to see if the new term satisfies the condition following the optional ones in the pattern.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~.I Reading A Word -", "sec_num": null }, { "text": "When a pattern has been matched completely, PHRAN continues checking all the other patterns on the pattern-list.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "When it has finished, PHRAN will take the longest pattern that was matched and will consider the concept of its pattern-concept pair to be the meaning of the sequence.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "If there are several patterns of the same length :hat we re matched PHRAN will group all their meanings together.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "New patterns are suggested end a disembiguation process follows, exactly as in the case of a new word being read.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "For example, the words \"the big apple\", when recognized, will have two possible meanings: one being a large fruit, the other being New York Clty, PHRAN will check the patterns active at that time %0 determine if one of these two meanings satisfies the next condition in one of the patterns.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "If so, then that meaning will be chosen, Otherwise 'a large fruit' will be the default, as it is the first in the list of possible meanings.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "a.3.2 A Pattern Is Matched -", "sec_num": null }, { "text": "In certain cases there is need for slightly modified notions of pattern and concept, the most prominent examples being adverbs and adverbial phrases. Such phrases are also recognized through the use of patterns. However, upon recognizing an adverb, PHRAN searches within the active patterns for an action that it can modify.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "When such an action is found the concept part of the pair associated with the adverb is used to modify the concept of the original action.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "Adverbs such as \"quickly\"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "and \"slowly\" are currently defined and can be used to modify conceptualizations containing various actions.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "Thus PHRAN can handle constructs like:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "John ate slowly. Ouickly, John left the house. John left the house quickly. John slowly ate the apple. John wanted slowly to eat the apple. Some special cases of negation are handled by specific patterns.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "For example, the negation of the verb want usually is interpreted ss meaning \"want not\" -\"~ didn't want to go ~o school\" means the same thing as \"Mary wanted not to go:to school\".", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "Thus PHRAN conzains the specifi~ pattern [ (do> \"not\" ! which Is associated with this interpretation.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "4.~ Adverbs And Adverbial Phrases", "sec_num": null }, { "text": "Retrieving the phrasal pattern matching a particular utterance from PHRAN's knowledge base is sn important problem that we have not yet solved to our complete satisfaction.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "~-5 Indexing And Pattern Suggestion", "sec_num": null }, { "text": "We find some consolation in the fact that the problem of indexing a large data base is a neccesary and familiar problem for all Enowledge based systems.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "~-5 Indexing And Pattern Suggestion", "sec_num": null }, { "text": "We have tried two pattern suggestion mechanisms with PHRAN: I. Keying oatterns off individual words or previously matched patterns.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "~-5 Indexing And Pattern Suggestion", "sec_num": null }, { "text": "go%ten from the sentence a~d phras~T paz~erns recognized in it.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "The first indexing mechanism works but it requires that any pattern used to recognize a phrasal expressions be suggested by some word in it. This is unacceptable because it will cause the pattern to be suggested whenever the word it is triggered by is mentioned. The difficulties inherent in such an indexing scheme can be appreciated by considering which word in the phrase \"by ana large\" should be used to trigger it. Any choice we make will cause the pattern ~o be suggested very often in contexts when it is not appropriate.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "~nthis form, FHRAN's ~rocessing roughly resembles ELI's (Riesbeck et el, 19V59. We therefore developed the second mechanism. The ~ atterns-concapt pairs of the database are indexed in s ree.", "cite_spans": [ { "start": 56, "end": 72, "text": "(Riesbeck et el,", "ref_id": null }, { "start": 73, "end": 79, "text": "19V59.", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "As words are read, the pattern suggesting mechanism travels down this tree, choosing branches according to the meanings of the words.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "It suggests to PHRAN the patterns found at the nodes it has arrived at. The list of nodes is remembered, and when the next word is read the routine continues to branch from them, in addition to starting from the root.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "In practice, the number of nodes in the list is rather smsll.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "For example, whenever a noun-phrase is followed by an active form of some verb, the suggesting routine instructs PHRAN to consider the simple declarative forms of the verb. When a noun-phrase is followed by the vero 'to be' followed by the perfective form of some verb, the routine instructs PHRAN to consider the passive uses of the last verb. The phrasal pattern that will recognize the expression \"by and large\" is found st the node reaches only after seeing those three woras consecutively.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "In this manner this pattern will be suggested only when neccessary.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "The main problem with this scheme is that it does not lend itself well to allowing contextual cues to influence the choice of patterns PHRAN should try. This is one area where future research will be concentrates.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Indexing patterns under ordered seouences of cues", "sec_num": "2." }, { "text": "There are a number of other natural lenguage processing systems that either use some notion of patterns or produce meaning structures as output.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "We contrast PHRAN w~th some of these.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "An example of a natural language understanding system that produces declarative meaning representations Ss Riesbeck's \"conceptual analyzer\" (Riesbeck, 1974 When a word is reed by the system, the routines associated with that word are used to build up a meaning structure that eventually denotes the messing of the entire utterance. 19~) . It receives a sentence as input and ,na]yzes it in several separate \"stages\". In effect, PARRY replaces the input wi~h sentences of successively simpler form. In %he simplified sentence PARRY searches for patterns, of which there ere two bssic types: patterns used to interpret the whole ~entence, snd those used on~y to interpret parts of ~t {relative clauses, for example).", "cite_spans": [ { "start": 140, "end": 155, "text": "(Riesbeck, 1974", "ref_id": null }, { "start": 332, "end": 336, "text": "19~)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "For PARRY, the purpose of the natural language analyzer is only to translate the input into a simplified form that a model of a paranoid person may use to determine an appropriate response. No attempt Js made to model the analyzer itself after a human language user, as we are doing, nor are claims made to this effect.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "A system attempting to model human language analysis could not permit several unre]e+ed passes, the use of s transition network grsmmsr to interpret only certain sub-strings in the input, or a rule permitting it to simply ignore parts of the input.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "This theoretical shortcoming of PARRY -hsving separate grammar rules for the complete sentence ~nd for sub-parts o\" it -is shsred by Henarix's LYFER (Hendrix. IO77) . LIFER is designed to enable a database to be queried usJn~ 8 subset of the English language.", "cite_spans": [ { "start": 149, "end": 164, "text": "(Hendrix. IO77)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "As is t~_ case for PARRY, the natural language ansAysis done by ~Ar~R is not meant to model humans.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "Rather, its function is to translate the input into instructions and produce s reply as efficiently es possible, and nothing resembling s representation of tne meaning of the input is ever l ormea, u: course the purpose of LIFE~ is not to be th ~ front end of a system that understands coherent texts and which must therefore perform subsequent inference processes.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "Wh~le LIFER provides s workable solution to the natural language problem in a limited context I msny general problems of language analysis are not adoresseo in that context. SOPHYE (Burton, 1976) was designed to assist students in learning about simple electronic circuits. It can conduct a dialogue with the user in a restricted subset of the English language, and it uses knowledge about patterns of speech to interpret the input. SOPHIE accepts only certain questions and instructions concerning a few tasks.", "cite_spans": [ { "start": 181, "end": 195, "text": "(Burton, 1976)", "ref_id": "BIBREF2" } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "As is the case with LI-FER. the langusge utterances acceptable to the system are restricted to such an extent that many natural language processing problems need not be deelt with and other problems have solutions appropriate only to this context. In addition, SOPHIE does not produce any representation of the meanin~ of the input, and it makes more than one pass on the Input i~morlng unknown words, practices that nave already been crlticized.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "The augmented finite state transition network (ATN) has been used by a number of researchers to aid in the analysis of natural language sentences (for example, see Woods 1970) .", "cite_spans": [ { "start": 164, "end": 175, "text": "Woods 1970)", "ref_id": "BIBREF13" } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "However, most systems that use ATN's incorporate one feature which we find objectioneble on both theoretical and practical grounds. This is the separation of analysis into syntactic and semantic phases.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "The efficacy and psychological validity of the separation of syntactic and sementicprocessing has been argued at lengthelsewhere (see Schar~ 1975 for example). In addition, most ATN based systems (for .xample Woods' LUNAR program) do not produce represents%ions, but rather, run queries of a data base.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "In contrast to the systems just described, Wilks' English-French machine ~ranslstor do~s not share several of their shortcomings (Wilks, 197~) . It produces a representation of the meaning of an utterance, and it attempts to deal with unrestricted natural language. The maxn difference between Wilk's system and system we describe is that Wilks' patterns are matched against concepts mentioned in a sentence.", "cite_spans": [ { "start": 129, "end": 136, "text": "(Wilks,", "ref_id": null }, { "start": 137, "end": 142, "text": "197~)", "ref_id": null }, { "start": 339, "end": 345, "text": "Wilks'", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "To recognize these concepts he attaches representations to words in e dictionary.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "The problem is that this presupposes that there is a simple correspondence between %he form of a concept and the form of a language utterance.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "However, it is the fact that this correspondence is not simple that leads to the difficulties we are addressing in our work. In fact, since the correspondence of words to meanings is complex, it would appear ~hat a program like Wilks' translator will even~ually need %he kind of knowledge embodied in PHRAN to complete its analysis.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null }, { "text": "One recent attempt at natural language analysis that radically departs f~om pattern-based approaches is Rieger ' and Small 's system (Smell, 1978) . This system uses word experts rather than patterns as its basic mechsnxsm. ~nelr system acknowledges the enormity of the knowledge base required for language understanding, and proposes s way of addressing the relevant issues. However, the idea of puttin~ as much information as possible under individual words is about as far from our -conception of language analysis as one can get, and we would argue, would exemplify all the problems we have described in word-based systems.", "cite_spans": [ { "start": 123, "end": 146, "text": "'s system (Smell, 1978)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "5.O COMPARISON TO OTHER SYSTEMS", "sec_num": null } ], "back_matter": [], "bib_entries": { "BIBREF0": { "ref_id": "b0", "title": "The phrssel lexicon", "authors": [ { "first": "Joseph", "middle": [ "D" ], "last": "Becket", "suffix": "" } ], "year": 1975, "venue": "Theoretical Issues in Natural Language Processing", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Becket, Joseph D. (1975). The phrssel lexicon. In Theoretical Issues in Natural Language Processing. R.", "links": null }, "BIBREF1": { "ref_id": "b1", "title": "Problems in conceptual analysis of natural lenguage", "authors": [ { "first": "L", "middle": [], "last": "Birnbaum", "suffix": "" }, { "first": "M", "middle": [], "last": "Selfridge", "suffix": "" } ], "year": 1979, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Birnbaum, L. and Selfridge, M. (1979). Problems in conceptual analysis of natural lenguage. Yale Un versity Department of Computer Science Research Report I~8.", "links": null }, "BIBREF2": { "ref_id": "b2", "title": "Semantic Grammar: An Engineering Technique for Constructing Natural Language Understanding Systems", "authors": [ { "first": "", "middle": [], "last": "Burton", "suffix": "" }, { "first": "R", "middle": [], "last": "Richard", "suffix": "" } ], "year": 1976, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Burton., Richard R. (1976). Semantic Grammar: An Engineering Technique for Constructing Natural Language Understanding Systems. BaN Report No. 3a53, Dec 1976.", "links": null }, "BIBREF3": { "ref_id": "b3", "title": "Innocence: A Second Idealization for Linguistics", "authors": [ { "first": "C", "middle": [ "J" ], "last": "Fillmore", "suffix": "" } ], "year": 1979, "venue": "Proceedings of the Fifth Berkeley Language Symposium, Ber~eiey, c~/l-iTE~nia", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Fillmore, C.J. (1979). Innocence: A Second Idealization for Linguistics. In Proceedings of the Fifth Berkeley Language Symposium, Ber~eiey, c~/l-iTE~nia.", "links": null }, "BIBREF4": { "ref_id": "b4", "title": "%e Lifer Menus]: A Guide to Building Practical Netursl Language Interfaces. SRY !nterns~ionel: AI Center Tachnicel Note 138", "authors": [ { "first": "Gary", "middle": [ "G" ], "last": "Hendrix", "suffix": "" } ], "year": 1977, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Hendrix, Gary G. (197\"). ~\"%e Lifer Menus]: A Guide to Building Practical Netursl Language Interfaces. SRY !nterns~ionel: AI Center Tachnicel Note 138, Feb 1977.", "links": null }, "BIBREF5": { "ref_id": "b5", "title": "Linguistic", "authors": [ { "first": "T", "middle": [ "F" ], "last": "Mitchell", "suffix": "" } ], "year": 1971, "venue": "Goings On", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Mitchell, T. F. (1971). Linguistic \"Goings On\";", "links": null }, "BIBREF6": { "ref_id": "b6", "title": "Collocations and Other Matters Arising on th~ Syntactic Record. Arch~vum Linguisticum 2 (new series", "authors": [], "year": null, "venue": "", "volume": "7", "issue": "", "pages": "3--69", "other_ids": {}, "num": null, "urls": [], "raw_text": "Collocations and Other Matters Arising on th~ Syntactic Record. Arch~vum Linguisticum 2 (new series 3~-69. IQ7", "links": null }, "BIBREF7": { "ref_id": "b7", "title": "~ \u2022 Conversational Language Comprehension Using Integrated Pattern-Matching and Parsing", "authors": [ { "first": "R", "middle": [ "C" ], "last": "P~rkinson", "suffix": "" }, { "first": "K", "middle": [ "M" ], "last": "Colby", "suffix": "" }, { "first": "W", "middle": [ "S" ], "last": "Faught", "suffix": "" } ], "year": null, "venue": "Artificial Inte", "volume": "9", "issue": "", "pages": "111--134", "other_ids": {}, "num": null, "urls": [], "raw_text": "P~rkinson, R.C., Colby, K.M., and Faught, W.S. ( . ~ \u2022 Conversational Language Comprehension Using Integrated Pattern-Matching and Parsing. Artificial Inte]ll~ence 9, 111-134.", "links": null }, "BIBREF8": { "ref_id": "b8", "title": "Conceptual anelysis. In R. C. Sohenk Conceptual Informetion Processing", "authors": [ { "first": "C", "middle": [ "K" ], "last": "Riesbeck", "suffix": "" } ], "year": 1975, "venue": "American Elsevier ~uoAlsoing uompany", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Riesbeck, C. K. (1975). Conceptual anelysis. In R. C. Sohenk Conceptual Informetion Processing. American Elsevier ~uoAlsoing uompany, ~nc,, Sew York.", "links": null }, "BIBREF9": { "ref_id": "b9", "title": "Comprehension by computer: expectation-based analysis of sentences in context", "authors": [ { "first": "C", "middle": [ "K" ], "last": "R~esbeck", "suffix": "" }, { "first": "R", "middle": [ "C" ], "last": "Schank", "suffix": "" } ], "year": 1975, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "R~esbeck C. K. and Schank, R. C. (1975). Comprehension by computer: expectation-based analysis of sentences in context. Yale University Resesrch Report 78.", "links": null }, "BIBREF10": { "ref_id": "b10", "title": "Conceptual Information Processing", "authors": [ { "first": "", "middle": [ "R C" ], "last": "Schank", "suffix": "" } ], "year": 1975, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Schank. R. C. (1975). Conceptual Information Processing. American Elsevler ~uollsnlng 5ompeny, Inc., Row lOr~.", "links": null }, "BIBREF11": { "ref_id": "b11", "title": "Concegtuel language analysis for story comprehension", "authors": [ { "first": "S", "middle": [], "last": "Small", "suffix": "" } ], "year": 1978, "venue": "", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Small, S. (1978). Concegtuel language analysis for story comprehension. Technical Repor~ No. 565, Dept. of Computer Science, University of Maryland, College Park, Maryland.", "links": null }, "BIBREF12": { "ref_id": "b12", "title": "An AI Approach to Machine Translation", "authors": [ { "first": "Yorick", "middle": [], "last": "Wilks", "suffix": "" } ], "year": 1973, "venue": "Computer Models of Thought and Language", "volume": "", "issue": "", "pages": "", "other_ids": {}, "num": null, "urls": [], "raw_text": "Wilks, Yorick (1973). An AI Approach to Machine Translation. In Computer Models of Thought and Language, R.C. Schsnk and K.~. uoioy L eds.-'T, w.H. :foeman and Co., San Francisco, 1973.", "links": null }, "BIBREF13": { "ref_id": "b13", "title": "Transition Network Grommets for Natural Language Anelysis", "authors": [ { "first": "W", "middle": [ "A" ], "last": "Woods", "suffix": "" } ], "year": 1970, "venue": "CACM", "volume": "13", "issue": "", "pages": "591--606", "other_ids": {}, "num": null, "urls": [], "raw_text": "Woods, W. A. (1970). Transition Network Grommets for Natural Language Anelysis. CACM 13, 591-606.", "links": null } }, "ref_entries": { "FIGREF0": { "uris": null, "text": "CD-FORM '(INGEST (ACTO~ ?ACTOR) (OBJECT ?FOOD)) ACTOR (VAL~ I CD-FORM) FOOD 'FOOD])", "type_str": "figure", "num": null }, "TABREF4": { "type_str": "table", "html": null, "content": "
The new term is added to
*CONCEPT*, now:
< ~JOHNI -person ~V2 ] ,~[DROP -verb] , [OUT]
[0FT , [HIGH -sdjl , [SCHOOL -sch6ol, noun]'>
", "num": null, "text": "high .... school\" ] [ represention denoting a school $o~ IOth through 12th graders~ | 2. I [ ~noun>] [ representation denoting noun modified by adjectiveJ 1 Both patterns are satisfied by the previous term and this fact is stored under it." } } } }