Open Information Extraction

Model Name:*

Description with Markdown (optional):

# Summary

A reimplementation of a deep BiLSTM sequence prediction model (Stanovsky et al., 2018).

[Explore live Open Information Extraction demo at AllenNLP](https://demo.allennlp.org/open-information-extraction/open-information-extraction).

## How do I load this model?

```python
from allennlp_models.pretrained import load_predictor
predictor = load_predictor("structured-prediction-srl")
```

### Getting predictions

```python
sentence = "John broke the window with a rock."
preds = predictor.predict(sentence)
print(preds["verbs"][0]["description"])
# prints:
# [ARG0: John] [V: broke] [ARG1: the window] [ARGM-MNR: with a rock] .
```

You can also get predictions using allennlp command line interface:

```shell
echo '{"sentence": "John broke the window with a rock."}' | \
    allennlp predict https://storage.googleapis.com/allennlp-public-models/openie-model.2020.03.26.tar.gz -
```

## How do I train this model?

To train this model you can use `allennlp` CLI tool and the configuration file [srl.jsonnet](https://raw.githubusercontent.com/allenai/allennlp-models/v2.1.0/training_config/structured-prediction/srl.jsonnet):

```shell
allennlp train srl.jsonnet -s output_dir
```

See the [AllenNLP Training and prediction](https://guide.allennlp.org/training-and-prediction#2) guide for more details.

## Citation

```bibtex
@inproceedings{Stanovsky2018SupervisedOI,
 author = {Gabriel Stanovsky and Julian Michael and Luke Zettlemoyer and I. Dagan},
 booktitle = {NAACL-HLT},
 title = {Supervised Open Information Extraction},
 year = {2018}
}
```

Paper:*

Code URL (optional):

Epochs	500
Batch Size	80
Encoder Type	alternating_lstm
Encoder Layers	8
Encoder Input Size	200
Encoder Hidden Size	300

Training Techniques	AdaDelta
Architecture	Dropout, Linear Layer
Epochs	500
Batch Size	80
Encoder Type	alternating_lstm
Encoder Layers	8
Encoder Input Size	200
Encoder Hidden Size	300
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allenai / allennlp

Summary

How do I load this model?

Getting predictions

How do I train this model?

Citation