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

Autor: Yaqing Liu, Lidong Wang, Rong Chen, Yingjie Song, Yalin Cai
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Entropy, Vol 18, Iss 6, p 235 (2016)
Druh dokumentu: article
ISSN: 1099-4300
DOI: 10.3390/e18060235
Popis: 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%.
Databáze: Directory of Open Access Journals