ISPRS International Journal of Geo-InformationGeographic Named Entity Recognition (Geo-NER) is a crucial task for extracting geography-related entities from unstructured text, and it plays an essential role in geographic information extraction and spatial semantic understanding.
Yuting Zhang +5 more
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A geolocated dataset of German news articles [PDF]
Scientific DataThe emergence of large language models and the exponential growth of digitized text data have revolutionized research methodologies across a broad range of social sciences.
Lukas Kriesch, Sebastian Losacker
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Construction of a Geological Fault Corpus and Named Entity Recognition [PDF]
Applied SciencesThe rapid and effective extraction of fault entities is a fundamental process in constructing a fault knowledge graph. As a key method for recording and preserving fault data, a fault investigation report holds significant potential for extracting ...
Huainuo Wang +3 more
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From Text to Map: Combing Named Entity Recognition and Geographic Information Systems
Code4Lib Journal, 2020 This tutorial shows readers how to leverage the power of named entity recognition (NER) and geographic information systems (GIS) to extract place names from text, geocode them, and create a public-facing map.
Charlie Harper, R. Benjamin Gorham
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Utilization of geocoding for mapping infrastructure impacts and mobility due to floods in indonesia based on twitter analytics [PDF]
JPPI (Jurnal Penelitian Pendidikan Indonesia)Flooding, a frequent natural disaster in Indonesia, is caused by several factors such as high-intensity rainfall, climate change, inadequate drainage and urban infrastructure challenges, impacting communities, infrastructure and economic activities.
Muhammad Imam Taufiq +1 more
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Geo-parsing and analysis of road traffic crash incidents for data-driven emergency response planning [PDF]
HeliyonRoad traffic crashes (RTCs) are a major public health concern worldwide, particularly in Nigeria, where road transport is the most common mode of transportation.
Patricia Ojonoka Idakwo +3 more
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Optimizing context-based location extraction by tuning open-source LLMs with RAG [PDF]
International Journal of Digital EarthText data such as news from media include different types of geographic information, represented by location, that indicates the whereabout of events or phenomena.
Zifu Wang +12 more
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Normalisation of 16th and 17th century texts in French and geographical named entity recognition [PDF]
Proceedings of the 4th ACM SIGSPATIAL Workshop on Geospatial Humanities, 2020 Both statistical and rule-based methods for named entity recognition are quite sensitive to the type of language used in the analysed texts. Former studies have shown for example that it was harder to detect named entities in SMS or microblog messages where words are abridged or changed to lowercase.
Kogkitsidou, Eleni, Gambette, Philippe
openaire +2 more sources
Automated recognition of geographical named entities in titles of Ukiyo-e prints
Digital Humanities Workshop, 2021 This paper investigates the application of Natural Language Processing as a means to study the relationship between topography and its visual renderings in early modern Japanese ukiyo-e landscape prints. We introduce a new dataset with titles of landscape prints that have been annotated by an art historian for any included place-names.
Machotka, Ewa +2 more
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Transformer based named entity recognition for place name extraction from unstructured text [PDF]
, 2022 Place names embedded in online natural language text present a useful source of geographic information. Despite this, many methods for the extraction of place names from text use pre-trained models that were not explicitly designed for this task.
Singleton, A +7 more
core +1 more source