A survey paper for overview: Wei, Xiang & Wang, Bang. (2019). A Survey of Event Extraction from Text. IEEE.
https://www.researchgate.net/publication/337638438_A_Survey_of_Event_Extraction_from_Text
https://www.dmp.wa.gov.au/WAMEX-Minerals-Exploration-1476.aspx
source/20news_classification.ipynb
Source: https://blogs.sas.com/content/subconsciousmusings/files/2017/04/machine-learning-cheet-sheet-2.png
2. source/extract_event_example.ipynb is a simple example file to extract events using pattern matching (trigger words)
- Detect events using trigger words
- Extract event details
- Extract entities using a domain dictionary source/VOCABULARY_TYPED.json (https://github.com/majiga/OzROCK labelled dataset can be used for supervised named entity recognition; Dictionary folder also contains the 6 lists of entities.)
- Extract relations
- Build a graph and visualise
-
Visualise the events on the WA map (data/map_WA.csv file can be useful for getting latitude and longitude data)
Some graph visualisation that were created from mineral exploration reports: https://sites.google.com/view/majiga/case-studies
Graph from text demo: https://nlp-tlp.org/text2kg/
- Source code for the demo: https://github.com/majiga/text2kg-uwa
- Paper for the demo: https://arxiv.org/pdf/1909.01807.pdf
spacy.io
- List of events with their details
- Visualisations to explore or discover events
- Analysis, ...
- Check other required outcomes stated by the unit in https://handbooks.uwa.edu.au/unitdetails?code=CITS5553