-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathREADME
83 lines (63 loc) · 2.39 KB
/
README
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
-----------------------------------------------------------------
README - Domain Labeling
Sapienza NLP Group
Sapienza University of Rome
http://nlp.uniroma1.it
-----------------------------------------------------------------
This package contains a software whose function is to
automatically tag dictionary glosses with domains of knowledge
labels.
The software exploits the representational power of
multilingual BERT (M-BERT) and makes use of a simple yet
efficient Sequence Classification architecture, composed of a
multilingual BERT encoder -- which encodes the input -- and a
linear layer, to perform the classification.
--------
CONTENTS
--------
This package contains the following components:
├── config
│ └── custom.jsonnet # base jsonnet configuration file
├── data # folder for data
├── LICENSE
├── models
│ ├── released # folder for released models
│ └── trained # folder for trained models
├── src # source code
│ ├── allen_elements # allennlp-related code
│ ├── serve.py # simple cli interactive demo
│ └── main.py # training entry point
├── requirements.txt
├── README
└── USAGE.md
------------
REQUIREMENTS
------------
A python 3.7 installation (possibly in an environment manager).
------------
INSTALLATION
------------
Before running the following command, it is advised to create a new environment
(e.g., with conda) to avoid conflicts with your current one.
Install requirements via pip install -r requirements.txt.
The code is based off of AllenNLP's library. See usage instructions at USAGE.md.
-------
AUTHORS
-------
Federico Martelli, Sapienza University of Rome
Roberto Navigli, Sapienza University of Rome
Acknowledgments go to Niccolò Campolungo, Babelscape
([email protected]), for his contribution to the project.
---------
COPYRIGHT
---------
This software is licensed under a Creative Commons Attribution-Noncommercial-
Share Alike 4.0 License. See the LICENSE file for details.
---------------
ACKNOWLEDGMENTS
---------------
This software is an output of the ELEXIS project (https://elex.is). This project has
received funding from the European Union's Horizon 2020 research and innovation
programme under grant agreement No. 731015.