Abstract
The purpose of text geolocation is to associate geographic information contained in a document with a set (or sets) of coordinates, either implicitly by using linguistic features and/or explicitly by using geographic metadata combined with heuristics. We introduce a geocoder (location mention disambiguator) that achieves state-of-the-art (SOTA) results on three diverse datasets by exploiting the implicit lexical clues. Moreover, we propose a new method for systematic encoding of geographic metadata to generate two distinct views of the same text. To that end, we introduce the Map Vector (MapVec), a sparse representation obtained by plotting prior geographic probabilities, derived from population figures, on a World Map. We then integrate the implicit (language) and explicit (map) features to significantly improve a range of metrics. We also introduce an open-source dataset for geoparsing of news events covering global disease outbreaks and epidemics to help future evaluation in geoparsing.- Anthology ID:
- P18-1119
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1285–1296
- Language:
- URL:
- https://aclanthology.org/P18-1119
- DOI:
- 10.18653/v1/P18-1119
- Cite (ACL):
- Milan Gritta, Mohammad Taher Pilehvar, and Nigel Collier. 2018. Which Melbourne? Augmenting Geocoding with Maps. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1285–1296, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Which Melbourne? Augmenting Geocoding with Maps (Gritta et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/P18-1119.pdf