Web API specifications are machine-readable descriptions of APIs. These specifications, in combination with related tooling, simplify and support the consumption of APIs. However, despite the increased distribution of web APIs, specifications are rare and their creation and maintenance heavily rely on manual efforts by third parties. In this paper, we propose an automatic approach and an associated tool called D2Spec for extracting significant parts of such specifications from web API documentation pages. Given a seed online documentation page of an API, D2Spec first crawls all documentation pages on the API, and then uses a set of machine-learning techniques to extract the base URL, path templates, and HTTP methods - collectively describing the endpoints of the API. We evaluate whether D2Spec can accurately extract endpoints from documentation on 116 web APIs. The results show that D2Spec achieves a precision of 87.1% in identifying base URLs, a precision of 80.3% and a recall of 80.9% in generating path templates, and a precision of 83.8% and a recall of 77.2% in extracting HTTP methods. In addition, in an evaluation on 64 APIs with pre-existing API specifications, D2Spec revealed many inconsistencies between web API documentation and their corresponding publicly available specifications. API consumers would benefit from D2Spec pointing them to, and allowing them thus to fix, such inconsistencies.