https://github.com/s1998/re-label-noise
Code for modelling label noie in distantly supervised relation extraction
https://github.com/s1998/re-label-noise
Last synced: over 1 year ago
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Code for modelling label noie in distantly supervised relation extraction
- Host: GitHub
- URL: https://github.com/s1998/re-label-noise
- Owner: s1998
- Created: 2019-06-02T10:56:14.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2022-10-11T17:23:38.000Z (almost 4 years ago)
- Last Synced: 2025-02-01T18:27:39.434Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 2.49 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Relation extraction (modelling the label noise)
Code for modelling label noie in distantly supervised relation extraction.
# Usage help
```
usage: main.py [-h] [--encoder ENCODER] [--selector SELECTOR]
[--loss_type LOSS_TYPE] [--bs_val BS_VAL] [--dataset DATASET]
[--chkpt_pt CHKPT_PT] [--l2_val L2_VAL]
Running code for relation extraction.
optional arguments:
-h, --help show this help message and exit
--encoder ENCODER select the encoders from pcnn ,pbrnn ,pcnn2 (stacked
pcnn) ,rnn ,brnn ,crnn ,crnn2 ,bgwa
--selector SELECTOR select the bag selector from att, cross_sent_max
--loss_type LOSS_TYPE
select the loss type from none, extra (layer for noise
modelling), hard (bootstrapping), soft (bootstrapping)
--bs_val BS_VAL select the bootstrapping value (only valid if loss is
of type hard/soft)
--dataset DATASET select the dataset from nyt/wiki
--chkpt_pt CHKPT_PT path to saved model (empty if no checkpoint to load
from)
--l2_val L2_VAL l2 lambda value
```
# Results
Results on NYT dataset
## Results for cross senence maxpooling on NYT dataset
```
Encoder | Selector | AUC
---------------------------------
pcnn | att | 0.338
rnn | att | 0.333
brnn | att | 0.344
pcnn | cross-sent-max | 0.369
rnn | cross-sent-max | 0.385
brnn | cross-sent-max | 0.383
```
## Results for modelling label noise on NYT dataset
```
Mechanism | AUC
----------------------------------
PCNN + ATT | 0.338
PCNN + ATT + extra_layer | 0.348
```
We found that value of AUC score decreased for bootsrapping methods both hard and soft.
# References
1. [THUNLP's relation extraction](https://github.com/thunlp/OpenNRE)
2. [Adversarial methods for relation extraction](https://github.com/jxwuyi/AtNRE)
3. [Soft label methods fro relation extraction](https://github.com/tyliupku/soft-label-RE)