A PUT-Based Approach to Automatically Extracting Quantities and Generating Final Answers for Numerical Attributes

Abstract

Automatically extracting quantities and generating final answers for numerical attributes is very useful in many occasions, including question answering, image processing, human-computer interaction, etc. A common approach is to learn linguistics templates or wrappers and employ some algorithm or model to generate a final answer. However, building linguistics templates or wrappers is a tough task for builders. In addition, linguistics templates or wrappers are domain-dependent. To make the builder escape from building linguistics templates or wrappers, we propose a new approach to final answer generation based on Predicates-Units Table (PUT), a mini domain-independent knowledge base. It is deserved to point out that, in the following cases, quantities are not represented well. Quantities are absent of units. Quantities are perhaps wrong for a given question. Even if all of them are represented well, their units are perhaps inconsistent. These cases have a strong impact on final answer solving. One thousand nine hundred twenty-six real queries are employed to test the proposed method, and the experimental results show that the average correctness ratio of our approach is 87.1%.

Keywords

• numerical attribute
• information extraction
• quantity
• entity extraction