Papers by Ewan Oglethorpe
MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization (2021.eacl-main)
Copied to clipboard
| Challenge: | a new multilingual summarization model is being developed to help humanitarian experts process large amounts of secondary data to derive situational awareness and guide decision-making. |
| Approach: | They propose to use multilingual documents and annotated snippets to improve extraction of secondary data for humanitarian response experts. |
| Outcome: | The proposed model provides multilingual documents with informative snippets that have been annotated by humanitarian analysts over the past four years. |
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crises Response (2022.findings-emnlp)
Copied to clipboard
Selim Fekih, Nicolo’ Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe, Navid Rekabsaz
| Challenge: | During humanitarian crises, a quick and accurate analysis of relevant data is critical to a timely and effective response. |
| Approach: | They introduce and release a multilingual dataset of humanitarian response documents annotated by experts in the humanitarian response domain. |
| Outcome: | The proposed dataset provides documents in three languages and covers a variety of humanitarian crises from 2018 to 2021 across the globe. |