# Within-Document Arabic Event Coreference: Challenges, Datasets, Approaches and Future Direction
## 2 Various Approaches and Data  
### Data  
When it comes to EC resolution, the English language domain faces several major challenges. Additionally, there are a variety of annotation schemas, topologies, and conceptual definitions of what an event is available in the corpora. Therefore, event coreference methodologies cannot be used to compare datasets for which they were not designed. A benchmark for entity and event coreference resolution systems in the English language domain has long been the OntoNotes corpus [5]. The large-scale multi-domain text collection contains annotations at the entity and event levels. Additionally, OntoNotes does not distinguish between entity and event labels: both are simply referred to as mentions. In spite of the fact that event coreference and entity coreference share many aspects, researchers currently face vastly different challenges when it comes to the two tasks. Additionally, verbal events cannot be classified as a single-word mention in the OntoNotes corpus unless there is an equivalent noun phrase. The data become less consistent as a result, especially since coreference resolution algorithms are intended for use in practical, real-world applications.  
Table 4 shows the available English corpora annotated with event reference relations and Table 5 presents the state-of-the-art systems for these corpora. The ACE 2005 [1] is used for evaluating the ACE corpora. A set of predefined type actions in English and Chinese are annotated as events and coreferences within the ACE 2005 corpus. In spite of the fact that ACE's event schema is relatively limited, its general approach has evolved over time. ACE methodology, for example, is incorporated into the TAC-KBP corpora [6], which combine ACE's typology with more complex and informative annotation styles. There are documents included in this dataset in English, Arabic, Chinese, and Spanish, as well as co-referential links within each document. These datasets all annotate co-referential links within documents, which makes cross-document event correlative resolution even more challenging. A monolingual English ECB+ corpus [7] is the standard for cross-document research, extending the more limited ECB corpus [8]. This corpus contains a substantial number of newspaper documents that contain multi-word event spans that have been annotated according to Rich ERE guidelines [9]. In addition to the use of a semi-automated data leveraging method, the WEC-Eng project developed the WEC-Eng dataset [10], the second and final cross-document English corpus. As a result of this method, event mentions and references are not limited to predefined categories. English, Dutch, Spanish, and Italian annotations are provided at the cross-document level. In terms of coverage, the dataset is largely unrestricted. Authors [10], proposed an efficient method for acquiring a large-scale dataset for cross-document event correlation is using Wikipedia's event conference.  
Several datasets are available in different languages, including Chinese [1,11], Greek [12], and Spanish [1,13]. Based on the available information at present, it has been ascertained that there are no existing corpora specifically annotated for Arabic event coreference. Therefore, there is no system yet to detect Arabic event coreference.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Dataset** & **Docs** & **Events Mentions** & **Chains** \\ \hline ACE 2005 & 599 & 5349 & 4090 \\ \hline ECB+ [7] & 982 & 14,884 & 9875 \\ \hline TAC KBP [11] & 1075 & 29,471 & 19,257 \\ \hline MAVEN-ERE [14] & 4480 & 112,276 & 103,193 \\ \hline \end{tabular}
\end{table}
Table 4: Statistics of the commonly used English corpora annotated with event coreference relation [14].