Extracting Space Situational Awareness Events from News Text
Zhengnan Xie, Alice Saebom Kwak, Enfa George, Laura W. Dozal, Hoang Van, Moriba Jah, Roberto Furfaro, Peter Jansen
Abstract
Space situational awareness typically makes use of physical measurements from radar, telescopes, and other assets to monitor satellites and other spacecraft for operational, navigational, and defense purposes. In this work we explore using textual input for the space situational awareness task. We construct a corpus of 48.5k news articles spanning all known active satellites between 2009 and 2020. Using a dependency-rule-based extraction system designed to target three high-impact events – spacecraft launches, failures, and decommissionings, we identify 1,787 space-event sentences that are then annotated by humans with 15.9k labels for event slots. We empirically demonstrate a state-of-the-art neural extraction system achieves an overall F1 between 53 and 91 per slot for event extraction in this low-resource, high-impact domain.- Anthology ID:
- 2022.lrec-1.653
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6077–6082
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.653
- DOI:
- Cite (ACL):
- Zhengnan Xie, Alice Saebom Kwak, Enfa George, Laura W. Dozal, Hoang Van, Moriba Jah, Roberto Furfaro, and Peter Jansen. 2022. Extracting Space Situational Awareness Events from News Text. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6077–6082, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Extracting Space Situational Awareness Events from News Text (Xie et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.653.pdf
- Code
- cognitiveailab/ssa-corpus