Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Data-Centric Framework for Composable NLP Workflows   Empirical natural language processing (NLP) systems in application domains
(e.g., healthcare, finance, education) involve interoperation among multiple
components, ranging from data ingestion, human annotation, to text retrieval,
analysis, generation, and visualization. We establish a unified open-source
framework to support fast development of such sophisticated NLP workflows in a
composable manner. The framework introduces a uniform data representation to
encode heterogeneous results by a wide range of NLP tasks. It offers a large
repository of processors for NLP tasks, visualization, and annotation, which
can be easily assembled with full interoperability under the unified
representation. The highly extensible framework allows plugging in custom
processors from external off-the-shelf NLP and deep learning libraries. The
whole framework is delivered through two modularized yet integratable
open-source projects, namely Forte (for workflow infrastructure and NLP
function processors) and Stave (for user interaction, visualization, and
annotation).

18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
37
The categories of this paper are: supr-con