In linear regression, is there anything I can do if the coefficient for one of the features is unrealistic/inappropriate?
What could be happening here is multicollinearity - where some of your predictors are correlated. In this case, it is not unreasonable to think that square footage, number of beds and number of bathrooms are all positively correlated with each other. This is not a big deal if your main goal is to just predict house prices, but what multicollinearity does in essence is that it makes it 'harder' to estimate the actual coefficient values, so your interpretations of the coefficients can't carry as much weight. I suspect that using more data will indeed reduce the chance of this happening.