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Dialog-based LL
Text
NLP
|...
License: Unknown

Overview

The Dialog-based Language Learning dataset, designed to measure how well models can perform
at learning as a student given a teacher’s textual responses to the student’s answer (as well
as potentially receiving an external real-valued reward signal). Details and baseline results
on this dataset can be found in the paper:

Jason Weston. Dialog-based Language Learning, arXiv:1604.06045.

Here is an example dialog, the last number (0 or 1) is the external reward:

1 Mary moved to the bathroom.           0
2 John went to the hallway.             0
3 Where is Mary?        bathroom        0
4 That's right.         1
5 Daniel went back to the hallway.              0
6 Sandra moved to the garden.           0
7 Where is Daniel?      office  0
8 No, they are downstairs.              0
9 John moved to the office.             0
10 Sandra journeyed to the bathroom.            0
11 Where is Daniel?     office  0
12 No, they are downstairs.             0
13 Mary moved to the hallway.           0
14 Daniel travelled to the office.              0
15 Where is Daniel?     office  0
16 Correct!             1
17 John went back to the garden.                0
18 John moved to the bedroom.           0
19 Where is Sandra?     garden  0
20 No, they are upstairs.               0

Citation

Please use the following citation when referencing the dataset:

@inproceedings{weston2016dialog,
  title={Dialog-based language learning},
  author={Weston, Jason E},
  booktitle={Advances in Neural Information Processing Systems},
  pages={829--837},
  year={2016}
}
Data Summary
Type
Text,
Amount
--
Size
140.17MB
Provided by
Facebook Research
Giving people the power to build community through research and innovation
| Amount -- | Size 140.17MB
Dialog-based LL
Text
NLP
License: Unknown

Overview

The Dialog-based Language Learning dataset, designed to measure how well models can perform
at learning as a student given a teacher’s textual responses to the student’s answer (as well
as potentially receiving an external real-valued reward signal). Details and baseline results
on this dataset can be found in the paper:

Jason Weston. Dialog-based Language Learning, arXiv:1604.06045.

Here is an example dialog, the last number (0 or 1) is the external reward:

1 Mary moved to the bathroom.           0
2 John went to the hallway.             0
3 Where is Mary?        bathroom        0
4 That's right.         1
5 Daniel went back to the hallway.              0
6 Sandra moved to the garden.           0
7 Where is Daniel?      office  0
8 No, they are downstairs.              0
9 John moved to the office.             0
10 Sandra journeyed to the bathroom.            0
11 Where is Daniel?     office  0
12 No, they are downstairs.             0
13 Mary moved to the hallway.           0
14 Daniel travelled to the office.              0
15 Where is Daniel?     office  0
16 Correct!             1
17 John went back to the garden.                0
18 John moved to the bedroom.           0
19 Where is Sandra?     garden  0
20 No, they are upstairs.               0

Citation

Please use the following citation when referencing the dataset:

@inproceedings{weston2016dialog,
  title={Dialog-based language learning},
  author={Weston, Jason E},
  booktitle={Advances in Neural Information Processing Systems},
  pages={829--837},
  year={2016}
}
0
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