Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Enriching Large-Scale Eventuality Knowledge Graph with Entailment
  Relations   Computational and cognitive studies suggest that the abstraction of
eventualities (activities, states, and events) is crucial for humans to
understand daily eventualities. In this paper, we propose a scalable approach
to model the entailment relations between eventualities ("eat an apple''
entails ''eat fruit''). As a result, we construct a large-scale eventuality
entailment graph (EEG), which has 10 million eventuality nodes and 103 million
entailment edges. Detailed experiments and analysis demonstrate the
effectiveness of the proposed approach and quality of the resulting knowledge
graph. Our datasets and code are available at
https://github.com/HKUST-KnowComp/ASER-EEG.

37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas