Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Zero-Shot Information Extraction as a Unified Text-to-Triple Translation   We cast a suite of information extraction tasks into a text-to-triple
translation framework. Instead of solving each task relying on task-specific
datasets and models, we formalize the task as a translation between
task-specific input text and output triples. By taking the task-specific input,
we enable a task-agnostic translation by leveraging the latent knowledge that a
pre-trained language model has about the task. We further demonstrate that a
simple pre-training task of predicting which relational information corresponds
to which input text is an effective way to produce task-specific outputs. This
enables the zero-shot transfer of our framework to downstream tasks. We study
the zero-shot performance of this framework on open information extraction
(OIE2016, NYT, WEB, PENN), relation classification (FewRel and TACRED), and
factual probe (Google-RE and T-REx). The model transfers non-trivially to most
tasks and is often competitive with a fully supervised method without the need
for any task-specific training. For instance, we significantly outperform the
F1 score of the supervised open information extraction without needing to use
its training set.

26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-lat
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
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The categories of this paper are: adap-org