An Annotated Commodity News Corpus for Event Extraction
This provides a domain-specific resource for researchers in computational linguistics and finance, but it is incremental as it focuses on data creation rather than novel methods.
The authors tackled the lack of annotated data for event extraction in commodity news by introducing a new dataset with entities, events, metadata, and relations annotated, facilitating research in causal analysis and price prediction.
Commodity News contains a wealth of information such as sum-mary of the recent commodity price movement and notable events that led tothe movement. Through event extraction, useful information extracted fromcommodity news is extremely useful in mining for causal relation betweenevents and commodity price movement, which can be used for commodity priceprediction. To facilitate the future research, we introduce a new dataset withthe following information identified and annotated: (i) entities (both nomi-nal and named), (ii) events (trigger words and argument roles), (iii) eventmetadata: modality, polarity and intensity and (iv) event-event relations.