Menu-based NLUI System

AKA: Menu-based Natural Language Understanding System.
Example(s):
- NLMenu System,
- Symantec Q&A System.
- …
Counter-Example(s):
- a Dialogue-based NLUI System.
See: Natural Language Processiong System, Question Answering System, Natural Language Interface to Databases System, Natural Language Interface to Ontologies, Speech Recognition System, Information Retrieval System, Natural Language Understanding System, Natural Language Generation System.

References

(Androutsopoulos et al., 1995) ⇒ I. Androutsopoulos, G.D. Ritchie, and P. Thanisch. (1995). “Natural Language Interfaces to Databases - An Introduction.” In: Natural Language Engineering Journal, 1(1). Cambridge University Press. doi:10.1017/S135132490000005X
- QUOTE: In menu-based systems the user is not able to type directly his/her questions. Instead, each question has to be constructed by choosing possible words or phrases from menus. The menus are displayed on the screen, and they are continuously updated.

(Tennant et al., 1983) ⇒ Harry R. Tennant, Kenneth M. Ross, Richard M. Saenz, Craig W. Thompson, and James R. Miller. (1983). "Menu-based Natural Language Understanding".; In: Proceedings of the 21st annual meeting on Association for Computational Linguistics. doi:10.3115/981311.981341.
- QUOTE: Thus, the interface system must somehow make it clear to the user what the coverage of the system is. Rather than requiring the user to type his input to the natural language understanding system, the user is presented with a set of menus on the upper half of a high resolution bit map display. He can choose the words and phrases that make up his query with a mouse. As the user chooses items, they are inserted into a window on the lower half of the screen so that he can see the sentence he is constructing. As a sentence is constructed, the active menus and items in them change to reflect only. the legal choices, given the portion of the sentence that has already been input. At any point in the construction of a natural language sentence, only those words or phrases that could legally come next will be displayed for the user to select. Sentences which cannot be processed by the natural language system can never be input to the system, giving a 0% failure rate. In this way, the scope and limitations of the system are made immediately clear to the user and only understandable sentences can be input. Thus, all queries fall within the linguistic and conceptual coverage of the system.