Grosz, Barbara, Douglas Appelt, Paul Martin, and Fernando Pereira (1986). "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces". SRI Technical Note 356R.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....which the generation routine then uses as new goals. Related Work A variety of systems have used rules of the kind we are considering, either explicitly or implicitly, for use in understanding compounds, vague expres sions, and metonymy, for example, Dahl et al. 87] Hobbs et al. 88] Grosz et al. 85] Stallard 87] but no mention is made of reversing these rules for gen eration. A number of systems generate compounds, but most apparently do so using either phrasal lexi cons (e.g. Hovy 881, Jacobs 8861, Wilensky 881) or multiple lexical senses (e.g. Pustejovsky et al. 87] ....

B. Grosz, D. Appelt, P. Martin, and F. C. N. Peteira, "Team: An Experiment in the Design of Transportable Natural-Language Inter- faces", Artificial Intelligence.

....a more specific representation at the pragmatics level for inferencing. Reasoning about cumulative readings is particularly interesting, and I will discuss it in detail. 2 Model Based Reasoning for Disambiguation Although scope ambiguity has been worked on by many researchers (e.g. Grosz et al. [8]) the main problem addressed has been how to generate all the scope choices and order them according to some heuristics. This approach might be sufficient as far as scope ambiguity goes. However, collective distributive ambiguity subsumes scope ambiguity and a heuristics strategy would not be a ....

Barbara Grosz, Douglas Appelt, Paul Martin, and Fernando Pereira. Team: An experiment in the design of transportable natural-language interfaces. Artificial Intelligence, 32, 1987.

....istica la gu a. models [16] etc While powerful, these systems don t o#er theoretica gua ra tees,a ndaM ba E on very di#erentaE H; hms While there h a been extensive work on NLIs [2] most of theea: lier work is di#erent from our own precise is transportable toa] itra d a a a in the sense of [11],a nd in contra: with ha ndcraE ed sem a tic gra ma rs, whichaE taE[3;H to a individua l d a a a (e.g. LADDER [12] undergra dua te spent over 15 hours per da ta ba se to customize the Microsoft product 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 00 00 11 11 0 0 0 0 0 0 ....

B. Grosz, D. Appelt, P. Martin, and F. Pereira. TEAM: An Experiment in the Design of Transportable Natural Language Interfaces. In Artificial Intelligence 32,pages 173--243, 1987.

....A great deal of work has been done in constructing natural language interfaces to well structured underlying systems, such as data base systems. These natural language interfaces generally make use of an assumed system swucture, such as a schema, to define semantics [Martin, Appelt and Peteira 83; Grosz et al. 85] Woods et al. 72; Woods 73] Kaplan 79] On the other hand, almost no effort has been made in conslxucting natural language interfaces to systems that do not have such an extensive description, e.g. expert systems 2. The lack of such a schema means that there is no easy way to obtain ....

Grosz, B., Martin, P., Agpelt, D., Pereira, F.,Team: An Experiment in the Design of Transportable Natural Language Interfaces. Technical Report, SRI International, 1985.

....of knowledge that must be acquired is lexical information. This includes morphological information, syntactic categories, complement structure (if any) and pointers to semantic information associated with individual words. Acquiring lexical information may proceed by prompting a user, as in TEAM [13], IRUS [7] and JANUS [9] Alternatively, efforts are underway to acquire the information directly from on line dictionaries [3, 16] Semantic knowledge includes at least two kinds of information: selectional restrictions or case frame constraints which can serve as a filter on what makes sense ....

....tools, we describe where our work and the work of several other significant, recently reported systems fall in that space of pos sibilities. 3.1 Class of underlying systems. One could design tools for a specific subclass of underlying systems, such as database management systems, as in TEAM [13] and TELl [4] The special nature of the class of underlying systems may allow for a more tailored acquisition environment, by having special purpose, stereotypical sequences of questions for the user, and more powerful special purpose inferences. For example, in order to acquire the vadety of ....

Grosz, B., Appelt, D. E., Martin, P., and Pereira, F. TEAM: An Experiment in the Design of Transportable Natural Language Interfaces. 356, SRI International, 1985. To appear in Artificial Intelligence.

....systems which serve as interfaces to a database: the problems that arise in a module which maps the meaning representation to a second logical language for expressing actual database queries. A module performing such a mapping is a component of such question answering systems as TEAM [4], PHLIQA1 [7] and IRUS [1] As an example of difficulties which may be encountered, consider the question Was the patient s mother a diabetic whose logical representation must be mapped onto a particular boolean field which encodes for each patient whether or not this complex property is true. ....

Barbara Grosz, Douglas E. Appelt, Paul Martin, and Fernando Poreira. TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces. Technical Report 356, SRI International, Menlo Park, CA, August, 1985.

....corpora ( 31] 37] 68] 79] 88] 149] Another issue is how to cost effectively maintain a lexicon once it has been acquired. Most interfaces that have been built for users with no specialized linguistics training still look much like the first such interface created for the TEAM project ([93]) Other lexical interfaces are described in [17] 20] 71] 125] 90] 94] 92] 207] 206] The maintainer is presented with various sentences utilizing the word being updated and asked to indicate which usages are correct and which are not. Each sentence represents a test to determine ....

Barbara J. Grosz, Douglas E. Appelt, Paul. A. Martin, and Fernando C.N. Pereira. TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces. Artificial Intelligence, 32(2):173--243, 1987.

....corpora [31] 37] 68] 79] 88] 149] Another issue is how to cost effectively maintain a lexicon once it has been acquired. Most interfaces that have been built for users with no specialized linguistics training still look much like the first such interface created for the TEAM project [93]. Other lexical interfaces are described in [17] 20] 71] 90] 92] 94] 125] 209] 208] The maintainer is presented with various sentences utilizing the word being updated and asked to indicate which usages are correct and which are not. Each sentence represents a test to determine ....

Barbara J. Grosz, Douglas E. Appelt, Paul. A. Martin, and Fernando C.N. Pereira. TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces. Artificial Intelligence, 32(2):173--243, 1987.

.... NLIDBs into relational agents, and integrating languages and graphics that explore the advantages of both modalities [1,6] In order to guarantee a permanent adaptation of this type of solution to a dynamic domain one should consider two critical fundamental factors: extensibility and portability [9]. On the one hand, a product like a NLIDB has to guarantee the ease to increase the linguistic coverage related with the domain, without requiring a vast technical knowledge of the natural language. On the other hand, the system has to guarantee the portability to other databases, minimising the ....

Grosz, B. J., Appelt, D. E., Martin, P. A., Pereira, C. N. 1987. "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces". Artificial Intelligence 32, pages 173-243. Elsevier Science Publishers B.V. (North-Holland).

....is to provide users with the capability of obtaining information stored in a database [4] The user is not required to learn an artificial communication language, being possible to formulate questions in the user s own native language. Our solution has the advantage of being database independent [8]. ....

Grosz, B. J., Appelt, D. E., Martin, P. A., Pereira, C. N. 1987. "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces ". Artificial Intelligence 32, pages 173-243. Elsevier Science Publishers B.V. (NorthHolland) .

....a single application. The treatment of discourse phenomena, as well, was very dependent on the system s implementation and domain (e.g. LUNAR [14] LADDER [12] The subsequent generation of interfaces emphasized portability as a requirement for commercial viability (e.g. INTELLECT [10] TEAM [9]) The use of world models was reduced or eliminated, since they compromise the system s portability. As a consequence, the coverage of discourse phenomena was constrained. This paper presents a mechanism for pronominal anaphora resolution which was developed without recourse to world models, for ....

Grosz B., Appelt, D., Martin, P., Pereira, F.: TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces. Artificial Intelligence. 32 (1987) 173--243

....classes and closed classes. Open classes are: verbs, nouns and adjectives. Closed classes cover the functional categories: articles, numerals, pronouns, adverbs, prepositions, conjunctions and interjections [4] This classification of words has been largely used in natural language processing [2]. Almost all studies focus on open class word learning, since new words of a language almost always belong to these classes. 2. MORPHOLOGICAL ANALYZER The morphological analyzer prototype s basic objects (implemented in Smalltalk [1] are the words, its radicals and suffixes, and the ....

GROSZ, B.; APPELT, D.; MARTIN, P.; PEREIRA, F. TEAM: An Experiment in the Design of Transportable Natural Languages Interfaces. Artificial Intelligence 32:173-243, 1987.

....and so on. Some systems facilitate this process by including lexicons and morphology rules. A related issue is the kind of experience required to port systems, such as: knowledge of the particular systems involved, natural language processing experience, and general knowledge of database issues[GAMP87] CHAPTER 2. BACKGROUND 6 2.1.3 Natural Language Coverage One disadvantage of natural language interfaces is that they can only handle subsets of natural language[AR95] Furthermore, the linguistic coverage may be unclear to the enduser. MASQUE, for instance, can handle some kinds of ....

B. J. Grosz, D.E. Appelt, P.A. Martin, and F.C.N. Pereira. Team: An experiment in the design of transportable natural language interfaces. Artificial Intelligence, 32(2):173--243, 1987.

....to handle the kind of mal formed input expected from users, return a complete slot and filler construction and to do it fast enough to make a natural language front end a practical solution. The development of these kinds of natural language interfaces is well documented (Hendrix et al. 1978; Grosz et al. 1987; Alshawi, 1992) 3.2 Frontend Techniques 3.2.1 Brutal Parsing Parsing methods for handling real NLP applications are being developed all the time. Notably, there are methods such as the LR parsing algorithm (Tomita, 1985) phrasal parsing as seen in the SPARKLE project (Briscoe et al. 1997) ....

Grosz, B. J., D. E. Appelt, P. A. Martin, and F. C. N. Pereira. 1987. TEAM: An experiment in the design of transportable natural language interfaces. Artificial Intelligence, 32:173--243.

....Engine (CLARE) Alshawi et al., 1992) has a similar status with processing extended to domain reasoning, especially for pragmatic purposes. Though the distinction is essentially arbitrary, it is useful to make a working distinction, for evaluation purposes, between generic shells like the CLE, TEAM (Grosz et al., 1987), or Q A (Harvey, nd) and generic components exemplified by the Alvey NL Tools (Briscoe, 1992) consisting either of knowledge resources like grammars and lexicons, or of processors like parsers. Generic shells are intended, when instantiated, to subsume all the NLP for a system, and may indeed ....

B. Grosz et al, "TEAM: an experiment in the design of transportable natural-language interfaces", Artificial Intelligence 12, 1987, 173-243.

....the choice of where new concepts should be placed in the ontology. Thus, the composition as well as the adaptation of the ontology is facilitated. 8 Related Work The GETESS project builds on and extends a lot of earlier work in various domains. In the natural language community, research like [10] fostered the use of natural language application to databases, though these applications never reached the high precision and generality required in order to access typical databases, e.g. for accounting. Here, our approach seems better suited, since some of the deficits of natural language ....

B. Grosz, D. Appelt, P. Martin, and F. Pereira. Team: An experiment in the design of transportable natural-language interfaces. Artificial Intelligence, 32(2):173--243, 1987.

....statistical analyses of the text processing component for indicating frequent, though unmodelled, concepts and relations to the knowledge engineer. 7 Related Work The GETESS project builds on and extends a lot of earlier work in various domains. In the natural language community, research like (Grosz et al. 1987; Wahlster et al. 1978) fostered the use of natural language application to databases, though these applications never reached the high preciseness and generality required in order to access typical databases, e.g. for accounting. Here, our approach seems better suited, since the ....

Grosz, B., Appelt, D., Martin, P., & Pereira, F. (1987). Team: An experiment in the design of transportable natural-language interfaces. Artificial Intelligence, 32(2):173--243.

....easily be described by their input output behavior. 8.2 Transportable Natural Language Interfaces An important result of the SIS project is the annotation approach to the construction of transportable natural language interfaces. This section compares related approaches to this problem. TEAM [20] is probably the most sophisticated and well known transportable natural language interface. TEAM makes use of four knowledge sources: the augmented phrase structure grammar, the lexicon, the conceptual schema, and the database schema. The grammar is fixed and has a broad 4 Peter ....

B. Grosz, D. Appelt, P. Martin, and F. Pereira. TEAM: An experiment in the design of transportable natural language interfaces. Artificial Intelligence, 32(1987):173--243, 1987.

....chief method of acquiring information from the user is exemplar based; that is, it asks the user questions about the correctness of specific phrases or sentences, and draws the appropriate conclusions based on the responses. This approach is based on previous work done at SRI on the TEAM project [6]. The Wizard operates by obtaining a categorization of a new word, and by gradually refining the categorization through a series of questions. Each refinement of category, in turn, determines the subsequent questions to be asked. Each question asked is used to (1) refine the categorization of the ....

Barbara J. Grosz, Douglas E. Appelt, Paul Martin, and Fernando Pereira. TEAM: An experiment in the design of transportable natural-language interfaces. Technical Note 356R, Artificial Intelligence Center, SRI International, Menlo Park, California, 1987.

No context found.

Grosz, Barbara, Douglas Appelt, Paul Martin, and Fernando Pereira (1986). "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces". SRI Technical Note 356R.

No context found.

Barbara Grosz, Douglas E. Appelt, Paul A. Martin, and Fernando C.N. Pereira. TEAM: An experiment in the design of transportable natural-language interfaces. Artificial Intelligence, 32(2):173--243, 1987.

No context found.

Barbara Grosz, Doug Appelt, Paul Martin, and Fernando Pereira. TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces. Artificial Intelligence 32, pp. 173243, 1987.

No context found.

Grosz, B.J., D.E. Appelt, P.A. Martin, and F.C.N. Pereira. "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces". Artificial Intelligence 32 (1987), 173-243.

No context found.

Barbara J. Grosz, Douglas E. Appelt, Paul A. Martin, and Fernando C. N. Pereira. TEAM: An experiment in the design of transportable natural-language interfaces. Artificial Intelligence, 32(2):173--243, May 1987.

No context found.

Grosz, B. J., D. E. Appelt, P. Martin, and F. Pereira. 1987. "TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces ". Artificial Intelligence 32: 173--243.

First 50 documents

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC