This paper develops an efficient mechanism for extracting primary information requests from 'Seek-Object' type query messages. The mechanism consists of three steps. The first step extracts sentences which signal that the query is 'Seek-Object' type by recognizing distinctive surface expressions. The second step, biased by the expression patterns, analyzes their internal structures. The third step integrates these fragments by a partial discourse processing and represents writers' goal-directed information request; as these sentences often include referential expressions and the referred expressions are in background goal descriptions. We claim the mechanism can extract information requests fairly accurately, by showing evaluation results.