Correct predictions are in blue. If we detect only a subset of a labelled sentence, we highlight the caught part as blue, the missing part light blue. False positives are in green and false negatives are in red.

Problem Bid_Selection — Constraint detection

Several bidders are bidding for a large contract . The contract is divided into many tasks . Some tasks are critical and must be assigned to a bidder . Others are not critical and a penalty is charged if unassigned . Each bidder can bid for a subset of tasks and each task can be optional or mandatory in the bid . An optional task bid can be accepted separately , but mandatory task bids are all-or-nothing : mandatory tasks must be all accepted or all rejected for each bid . The objective is to find the cheapest assignment of tasks to bidders .

Problem Bid_Selection — Detection of the decisions and objects to be modeled

Several bidders are bidding for a large contract . The contract is divided into many tasks . Some tasks are critical and must be assigned to a bidder . Others are not critical and a penalty is charged if unassigned . Each bidder can bid for a subset of tasks and each task can be optional or mandatory in the bid . An optional task bid can be accepted separately , but mandatory task bids are all-or-nothing : mandatory tasks must be all accepted or all rejected for each bid . The objective is to find the cheapest assignment of tasks to bidders .

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