https://github.com/cyclecycle/role-pattern-nlp

Build and match patterns for semantic role labelling / information extraction with SpaCy
https://github.com/cyclecycle/role-pattern-nlp

nlp python semantic-role-labeling spacy

Last synced: 2 months ago
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Build and match patterns for semantic role labelling / information extraction with SpaCy

• Host: GitHub
• URL: https://github.com/cyclecycle/role-pattern-nlp
• Owner: cyclecycle
• License: mit
• Created: 2019-05-22T05:56:17.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T05:47:08.000Z (about 2 years ago)
• Last Synced: 2024-09-29T13:01:17.941Z (3 months ago)
• Topics: nlp, python, semantic-role-labeling, spacy
• Language: Python
• Homepage:
• Size: 5.16 MB
• Stars: 7
• Watchers: 1
• Forks: 2
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
d# Role Pattern

Build and match linguistic patterns for role labelling. Provides an example-driven approach to generate and refine patterns.

Uses graph-based pattern matching, built on SpaCy.

## Installation

With pip:

```

pip install role-pattern-nlp

```

## Example usage

```python

# First, parse a string to create a SpaCy Doc object

import en_core_web_sm

text = "Forging involves the shaping of metal using localized compressive forces."

nlp = en_core_web_sm.load()

doc = nlp(text)

from role_pattern_nlp import RolePatternBuilder

# Provide an example by mapping role labels to tokens

match_example = {

    'arg1': [doc[0]],  # [Forging]

    'pred': [doc[1]],  # [involves]

    'arg2': [doc[3]],  # [shaping]

}

''' Create a dictionary of all the features we want the RolePatternBuilder to have access to

when building and refining patterns '''

feature_dict = {'DEP': 'dep_', 'TAG': 'tag_'}

# Instantiate the pattern builder

role_pattern_builder = RolePatternBuilder(feature_dict)

#  Build a pattern. It will use all the features in the feature_dict by default

role_pattern = role_pattern_builder.build(match_example)  

# Match against any doc with the role_pattern

matches = role_pattern.match(doc)

print(matches)

'''

[{'arg1': [Forging], 'arg2': [shaping], 'pred': [involves]}]

'''

```

See examples/ for demonstration as to how to refine a pattern using negative examples.

## API

### RolePattern

#### RolePattern.spacy_dep_pattern

The dependency pattern in the form used to create the SpaCy DependencyMatcher object.

#### RolePattern.token_labels

The list of labels that corresponds to the tokens matched by the pattern.

## Built with

- [SpaCy](https://spacy.io) - DependencyMatcher

- [SpaCy pattern builder](https://github.com/cyclecycle/spacy-pattern-builder)

- [networkx](https://github.com/networkx/networkx) - Used by SpaCy pattern builder