Table 6: Sources of error in LPS model
['Error-type', '% of errors', '% as the only error']
According to the above experiments, the performance of the LPS models was quite strong regardless of the chosen gold standard. However, there is always room for improvement. To provide an idea on the sources of error and guide further development of the models to fix the shortcomings of the current models, we conducted an error analysis to identify the most common mistakes made by the LPS models. A random sample of 300 misclassified sentences was chosen, and we asked our Annotator A to review them based on the type of error that the algorithm is making. In summary, the main sources of error turned out to be as follows: (i) the lack of knowledge on what is relevant for a company’s success (i.e. “inability to recognize significance of events” and “need for more context”); (ii) inability to assess the credibility of a sentence (i.e. “company talking in advertising like-tone about its own operations” or “positive convention of talking about something”); and (iii) the failure to identify what is new information (e.g., detection of changes in numbers, time expressions and detection of roles).