| A00-1022 | output of the linguistic pre - | processor | . Then each single document is |
| A00-1001 | prototypical natural language | processor | for English written in Prolog |
| A00-1001 | easily adaptable natural language | processor | . It consists of a general grammar |
| A83-1004 | is a general purpose language | processor | which builds a formal representation |
| A83-1004 | is a general purpose language | processor | which builds a formal representation |
| A83-1006 | , containing information about | processor | chips . In particular , the fields |
| A83-1002 | one of the first naturallanguage | processors | to be built for the purpose of |
| A00-1008 | user issues an utterance , the | processor | reduces it to one of a small |
| A83-1006 | example , " How many MOTOROLA | processors | are there ? " to get a count |
| A83-1006 | employees , students , ships , | processor | chips ) ; the fields of the file |
| A00-1023 | example , the key to a question | processor | is to identify the asking point |
| A83-1004 | London " is marked so that the post | processor | will be called . The post processor |
| A00-1001 | consisting of a dictionary , a lexical | processor | , a grammar and a parser . • |
| A83-1001 | two parts : a natural language | processor | for building a formal representation |
| A00-1010 | different approach . The discourse | processor | , called the state manager , |
| A00-1041 | Koresh ask the FBI for a word | processor | ? What are the Valdez Principles |
| A00-1021 | Koresh ask the FBI for a word | processor | ? Q : Name the first private |
| A00-1022 | includes a text tokenizer , a lexical | processor | and a chunk parser . The chunk |
| A83-1004 | two parts : a Natural Language | Processor | ( NLP ) and a data base application |
| A00-1016 | processing being handled by an offboard | processor | . Since the speech processing |
