  In China, construction accidents have killed more people than any other
industry since 2012. The factors which led to the accident have complex
interaction. Real data about accidents is the key to reveal the mechanism among
these factors. But the data from the questionnaire and interview has inherent
defects. Many behaviors that impact safety are illegal. In China, most of the
cases are from accident investigation reports. Finding out the cause of the
accident and liability affirmation are the core of incident investigation
reports. So the truth of some answers from the respondents is doubtful. With a
series of NLP technologies, in this paper, causal factors of construction
accidents are extracted and organized from Chinese incident case texts.
Finally, three kinds of neglected causal factors are discovered after data
analysis.
