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GeoAnnotator: A Collaborative Semi-Automatic Platform for Constructing Geo-Annotated Text Corpora

1
School of Electrical and Computer Engineering, Purdue University, IN 47907, USA
2
Department of Geography, Penn State, PA 16802, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(4), 161; https://doi.org/10.3390/ijgi8040161
Received: 29 November 2018 / Revised: 11 February 2019 / Accepted: 15 March 2019 / Published: 27 March 2019
(This article belongs to the Special Issue Human-Centered Geovisual Analytics and Visuospatial Display Design)
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Abstract

Ground-truth datasets are essential for the training and evaluation of any automated algorithm. As such, gold-standard annotated corpora underlie most advances in natural language processing (NLP). However, only a few relatively small (geo-)annotated datasets are available for geoparsing, i.e., the automatic recognition and geolocation of place references in unstructured text. The creation of geoparsing corpora that include both the recognition of place names in text and matching of those names to toponyms in a geographic gazetteer (a process we call geo-annotation), is a laborious, time-consuming and expensive task. The field lacks efficient geo-annotation tools to support corpus building and lacks design guidelines for the development of such tools. Here, we present the iterative design of GeoAnnotator, a web-based, semi-automatic and collaborative visual analytics platform for geo-annotation. GeoAnnotator facilitates collaborative, multi-annotator creation of large corpora of geo-annotated text by generating computationally-generated pre-annotations that can be improved by human-annotator users. The resulting corpora can be used in improving and benchmarking geoparsing algorithms as well as various other spatial language-related methods. Further, the iterative design process and the resulting design decisions can be used in annotation platforms tailored for other application domains of NLP. View Full-Text
Keywords: geoparsing; iterative design; design guidelines; annotation; corpus; spatial linguistics; geographic information retrieval geoparsing; iterative design; design guidelines; annotation; corpus; spatial linguistics; geographic information retrieval
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Karimzadeh, M.; MacEachren, A.M. GeoAnnotator: A Collaborative Semi-Automatic Platform for Constructing Geo-Annotated Text Corpora. ISPRS Int. J. Geo-Inf. 2019, 8, 161.

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