Statistical approaches to processing Lexical Functional Grammars (LFG-DOP, [1]) require large corpora of text annotated with c-structure and f-structure representations. To date, such corpora that exist are constructed manually or semi-automatically. Manual construction is both time-consuming and error-prone. Semi-automatic construction usually proceeds as follows: an existing LFG grammar is used to parse input text. Typically, for each sentence in the input text, parsing will produce a large number of c- and f-structure analyses. A linguistic expert then inspects the analyses and for each sentence in the input text selects the single best analysis for the case at hand. For large grammars this can involve inspection of hundreds or thousands of proposed analyses for a single input sentence. In the present paper we develop an alternative, semi-automatic methodology that as much as possible avoids manual inspection of analyses for best fit. As input, the method requires a treeb...