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.
One example is below.
Q: 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.
A: A Neural Local Coherence Model
Rationale: 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
Q: This paper contains analysis and extension of exploiters-based knowledge extraction methods, which allow generation of new knowledge, based on the basic ones. The main achievement of the paper is useful features of some universal exploiters proof, which allow extending set of basic classes and set of basic relations by finite set of new classes of objects and relations among them, which allow creating of complete lattice. Proposed approach gives an opportunity to compute quantity of new classes, which can be generated using it, and quantity of different types, which each of obtained classes describes; constructing of defined hierarchy of classes with determined subsumption relation; avoidance of some problems of inheritance and more efficient restoring of basic knowledge within the database.
A:
Object-Oriented Knowledge Extraction using Universal Exploiters