Recognition of Implicit Geographic Movement in Text

Scott Pezanowski, Prasenjit Mitra


Abstract
Analyzing the geographic movement of humans, animals, and other phenomena is a growing field of research. This research has benefited urban planning, logistics, animal migration understanding, and much more. Typically, the movement is captured as precise geographic coordinates and time stamps with Global Positioning Systems (GPS). Although some research uses computational techniques to take advantage of implicit movement in descriptions of route directions, hiking paths, and historical exploration routes, innovation would accelerate with a large and diverse corpus. We created a corpus of sentences labeled as describing geographic movement or not and including the type of entity moving. Creating this corpus proved difficult without any comparable corpora to start with, high human labeling costs, and since movement can at times be interpreted differently. To overcome these challenges, we developed an iterative process employing hand labeling, crowd voting for confirmation, and machine learning to predict more labels. By merging advances in word embeddings with traditional machine learning models and model ensembling, prediction accuracy is at an acceptable level to produce a large silver-standard corpus despite the small gold-standard corpus training set. Our corpus will likely benefit computational processing of geography in text and spatial cognition, in addition to detection of movement.
Anthology ID:
2020.lrec-1.252
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2054–2063
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.252
DOI:
Bibkey:
Cite (ACL):
Scott Pezanowski and Prasenjit Mitra. 2020. Recognition of Implicit Geographic Movement in Text. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2054–2063, Marseille, France. European Language Resources Association.
Cite (Informal):
Recognition of Implicit Geographic Movement in Text (Pezanowski & Mitra, LREC 2020)
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PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2020.lrec-1.252.pdf