Abstract
ATLIS (short for ATLIS Tags Locations in Strings) is a tool being developed using a maximum-entropy machine learning model for automatically identifying information relating to spatial and locational information in natural language text. It is being developed in parallel with the ISO-Space standard for annotation of spatial information (Pustejovsky, Moszkowicz & Verhagen 2011). The goal of ATLIS is to be able to take in a document as raw text and mark it up with ISO-Space annotation data, so that another program could use the information in a standardized format to reason about the semantics of the spatial information in the document. The tool (as well as ISO-Space itself) is still in the early stages of development. At present it implements a subset of the proposed ISO-Space annotation standard: it identifies expressions that refer to specific places, as well as identifying prepositional constructions that indicate a spatial relationship between two objects. In this paper, the structure of the ATLIS tool is presented, along with preliminary evaluations of its performance.- Anthology ID:
- L12-1610
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Mehmet Uğur Doğan, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 612–616
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/1022_Paper.pdf
- DOI:
- Cite (ACL):
- John Vogel, Marc Verhagen, and James Pustejovsky. 2012. ATLIS: Identifying Locational Information in Text Automatically. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 612–616, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- ATLIS: Identifying Locational Information in Text Automatically (Vogel et al., LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/1022_Paper.pdf