You can use the fundamental matrix to recover the camera matrices and triangulate the 3D points from their images. However, you must be aware that the reconstruction you will obtain will be a projective reconstruction and not a Euclidean one. This is useful if your goal is to measure projective invariants in the original scene such as the cross ratio, line intersections, etc. but it won't be enough to measure angles and distances (you will have to calibrate the cameras for that).
If you have access to Hartley and Zisserman's textbook, you can check section 9.5.3 where you will find what you need to go from the fundamental matrix to a pair of camera matrices that will allow you to compute a projective reconstruction (I believe the same content appears in section 6.4 of Yi Ma's book). Since the source code for the book's algorithms is available online, you may want to check the functions vgg_P_from_F, vgg_X_from_xP_lin, and vgg_X_from_xP_nonlin.
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