Teacher: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Teacher: Now, understand the problem? If you are still confused, see the following example:
We propose a local coherence model based on a convolutional neural network that operates over the entity grid representation of a text. The model captures long range entity transitions along with entity-specific features without loosing generalization, thanks to the power of distributed representation. We present a pairwise ranking method to train the model in an end-to-end fashion on a task and learn task-specific high level features. Our evaluation on three different coherence assessment tasks demonstrates that our model achieves state of the art results outperforming existing models by a good margin.
Solution: A Neural Local Coherence Model
Reason: This statement "A Neural Local Coherence Model" is taken from the subtext "convolutional neural network" and its explanation in the passage. This is a positive example because the title belongs to the mentions in the passage

Now, solve this instance: This paper presents an ontology-based approach for the design of a collaborative business process model (CBP). This CBP is considered as a specification of needs in order to build a collaboration information system (CIS) for a network of organisations. The study is a part of a model driven engineering approach of the CIS in a specific enterprise interoperability framework that will be summarised. An adaptation of the Business Process Modeling Notation (BPMN) is used to represent the CBP model. We develop a knowledge-based system (KbS) which is composed of three main parts: knowledge gathering, knowledge representation and reasoning, and collaborative business process modelling. The first part starts from a high abstraction level where knowledge from business partners is captured. A collaboration ontology is defined in order to provide a structure to store and use the knowledge captured. In parallel, we try to reuse generic existing knowledge about business processes from the MIT Process Handbook repository. This results in a collaboration process ontology that is also described. A set of rules is defined in order to extract knowledge about fragments of the CBP model from the two previous ontologies. These fragments are finally assembled in the third part of the KbS. A prototype of the KbS has been developed in order to implement and support this approach. The prototype is a computer-aided design tool of the CBP. In this paper, we will present the theoretical aspects of each part of this KbS as well as the tools that we developed and used in order to support its functionalities.
Student:
Knowledge-based system for collaborative process specification