rita-dsl 0.7.4

Description:

ritadsl 0.7.4

RITA DSL







This is a language, loosely based on language Apache UIMA RUTA, focused on writing manual language rules, which compiles into either spaCy compatible patterns, or pure regex. These patterns can be used for doing manual NER as well as used in other processes, like retokenizing and pure matching
An Introduction Video

Links

Website
Live Demo
Simple Chat bot example
Documentation
QuickStart
Language Syntax Plugin for IntelijJ based IDEs

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Install
pip install rita-dsl
Simple Rules example
rules = """
cuts = {"fitted", "wide-cut"}
lengths = {"short", "long", "calf-length", "knee-length"}
fabric_types = {"soft", "airy", "crinkled"}
fabrics = {"velour", "chiffon", "knit", "woven", "stretch"}

{IN_LIST(cuts)?, IN_LIST(lengths), WORD("dress")}->MARK("DRESS_TYPE")
{IN_LIST(lengths), IN_LIST(cuts), WORD("dress")}->MARK("DRESS_TYPE")
{IN_LIST(fabric_types)?, IN_LIST(fabrics)}->MARK("DRESS_FABRIC")
"""

Loading in spaCy
import spacy
from rita.shortcuts import setup_spacy


nlp = spacy.load("en")
setup_spacy(nlp, rules_string=rules)

And using it:
>>> r = nlp("She was wearing a short wide-cut dress")
>>> [{"label": e.label_, "text": e.text} for e in r.ents]
[{'label': 'DRESS_TYPE', 'text': 'short wide-cut dress'}]

Loading using Regex (standalone)
import rita

patterns = rita.compile_string(rules, use_engine="standalone")

And using it:
>>> list(patterns.execute("She was wearing a short wide-cut dress"))
[{'end': 38, 'label': 'DRESS_TYPE', 'start': 18, 'text': 'short wide-cut dress'}]