SYSTEM AND METHOD FOR FINDING THE MOST LIKELY ANSWER TO A NATURAL LANGUAGE QUESTION
First Claim
1. A method for selecting answers to natural language questions from a collection of textual documents comprising the steps of:
- extracting scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question;
scoring the possible answers using the extracted scoring features and a features scoring function; and
presenting the best scoring possible answer to the user with context from the passage containing the answer.
1 Assignment
0 Petitions
Accused Products
Abstract
Automated question answering is disclosed that relates to the selection of an answer to a question from a pool of potential answers which awe manually or automatically extracted from a large collection of textual documents. The a feature extraction component, a feature combination component, an answer selection component, and an answer presentation component, among others, are included. The input to the system is a set of one or more natural language questions and a collection of textual document The output is a (possibly ranked) set of factual answers to the questions, these answers being extracted from the document collection.
-
Citations
22 Claims
-
1. A method for selecting answers to natural language questions from a collection of textual documents comprising the steps of:
-
extracting scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question; scoring the possible answers using the extracted scoring features and a features scoring function; and presenting the best scoring possible answer to the user with context from the passage containing the answer. - View Dependent Claims (2, 3, 4, 5)
-
-
6. A method for selecting answers to natural language questions from a collection of textual documents comprising the steps of:
-
extracting scoring features from a candidate list of passages of possible answers, wherein said scoring feature is an average distance between the beginning of a candidate answer in a passage and words in said natural language question that appear in said passage, and wherein said average distance is measured in a count of words; scoring the possible answers using the extracted scoring features and a features scoring function; and presenting the best scoring possible answer to the user with context from the passage containing the answer. - View Dependent Claims (7, 8, 9, 10)
-
-
11. A system for selecting answers to natural language questions from a collection of textual documents, comprising:
-
a memory; and at least one processor, coupled to the memory, operative to; extract scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question; score the possible answers using the extracted scoring features and a features scoring function; and present the best scoring possible answer to the user with context from the passage containing the answer. - View Dependent Claims (12, 13, 14, 15)
-
-
16. A system for selecting answers to natural language questions from a collection of textual documents, comprising:
-
a memory; and at least one processor, coupled to the memory, operative to; extract scoring features from a candidate list of passages of possible answers, wherein said scoring feature is an average distance between the beginning of a candidate answer in a passage and words in said natural language question that appear in said passage, and wherein said average distance is measured in a count of words; score the possible answers using the extracted scoring features and a features scoring function; and present the best scoring possible answer to the user with context from the passage containing the answer. - View Dependent Claims (17, 18, 19, 20)
-
-
21. An article of manufacture for selecting answers to natural language questions from a collection of textual documents, comprising a machine readable medium containing one or more programs which when executed implement the steps of:
-
extracting scoring features from a candidate list of passages of possible answers, wherein said scoring feature is a number of words in a candidate answer that are different than words in said natural language question; scoring the possible answers using the extracted scoring features and a features scoring function; and presenting the best scoring possible answer to the user with context from the passage containing the answer.
-
-
22. A article of manufacture for selecting answers to natural language questions from a collection of textual documents, comprising a machine readable medium containing one or more programs which when executed implement the steps of:
-
extracting scoring features from a candidate list of passages of possible answers, wherein said scoring feature is an average distance between the beginning of a candidate answer in a passage and words in said natural language question that appear in said passage, and wherein said average distance is measured in a count of words; scoring the possible answers using the extracted scoring features and a features scoring function; and presenting the best scoring possible answer to the user with context from the passage containing the answer.
-
Specification