Abstract
Procedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable instructions have been useful learning resources for human, they are not interpretable by machines. Automatically acquiring procedural knowledge in machine interpretable formats from instructions has become an increasingly popular research topic due to their potential applications in process automation. However, it has been insufficiently addressed. This paper presents an approach and an implemented system to assist users to automatically acquire procedural knowledge in structured forms from instructions. We introduce a generic semantic representation of procedures for analysing instructions, using which natural language techniques are applied to automatically extract structured procedures from instructions. The method is evaluated in three domains to justify the generality of the proposed semantic representation as well as the effectiveness of the implemented automatic system.
Original language | English |
---|---|
Title of host publication | International Conference on Language Resources and Evaluation (LREC 2012) |
Editors | Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Mehmet U. Doğan, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis |
Pages | 520-527 |
Number of pages | 8 |
Publication status | Published - 2012 |
Event | 8th International Conference on Language Resources and Evaluation - Istanbul, Turkey Duration: 21 May 2012 → 27 May 2012 |
Conference
Conference | 8th International Conference on Language Resources and Evaluation |
---|---|
Abbreviated title | LREC 2012 |
Country/Territory | Turkey |
City | Istanbul |
Period | 21/05/12 → 27/05/12 |
Keywords
- procedural knowledge
- information extraction
- instructional text
Fingerprint
Dive into the research topics of 'Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing'. Together they form a unique fingerprint.Datasets
-
Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing
Zhang, Z. (Creator), Webster, P. (Creator), Uren, V. (Creator), Varga, A. (Creator) & Ciravegna, F. (Creator), Aston Data Explorer, 26 Oct 2018
DOI: 10.17036/researchdata.aston.ac.uk.00000386, https://www.aclweb.org/anthology/L12-1094/
Dataset