Description
This is the Multi-Label Text Classification model that can be used to identify up to 7 classes to facilitate analysis, discovery, and comparison of legal texts in French related to COVID-19 exception measures. The classes are as follows:
- Army_mobilization
- Closures/lockdown
- Government_oversight
- Restrictions_of_daily_liberties
- Restrictions_of_fundamental_rights_and_civil_liberties
- State_of_Emergency
- Suspension_of_international_cooperation_and_commitments
Predicted Entities
Army_mobilization, Closures/lockdown, Government_oversight, Restrictions_of_daily_liberties, Restrictions_of_fundamental_rights_and_civil_liberties, State_of_Emergency, Suspension_of_international_cooperation_and_commitments
How to use
document_assembler = nlp.DocumentAssembler() \
.setInputCol("text")\
.setOutputCol("document")
embeddings = nlp.BertSentenceEmbeddings.pretrained("sent_bert_use_cmlm_multi_base_br", "xx") \
.setInputCols("document") \
.setOutputCol("sentence_embeddings")
classifierdl = nlp.MultiClassifierDLModel.pretrained("legmulticlf_covid19_exceptions_french", "fr", "legal/models") \
.setInputCols(["sentence_embeddings"])
.setOutputCol("class")
clf_pipeline = nlp.Pipeline(
stages=[document_assembler,
embeddings,
classifierdl])
df = spark.createDataFrame([["Par dérogation à l'alinéa 1er, sont autorisés :- les cérémonies funéraires, mais uniquement en présence de 15 personnes maximum, et sans possibilité d'exposition du corps ;"]]).toDF("text")
model = clf_pipeline.fit(df)
result = model.transform(df)
result.select("text", "class.result").show(truncate=False)
Results
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------+
|text |result |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------+
|Par dérogation à l'alinéa 1er, sont autorisés :- les cérémonies funéraires, mais uniquement en présence de 15 personnes maximum, et sans possibilité d'exposition du corps ;|[Restrictions_of_fundamental_rights_and_civil_liberties, Restrictions_of_daily_liberties]|
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------+
Model Information
| Model Name: | legmulticlf_covid19_exceptions_french |
| Compatibility: | Legal NLP 1.0.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [sentence_embeddings] |
| Output Labels: | [class] |
| Language: | fr |
| Size: | 14.0 MB |
References
Train dataset available here
Benchmarking
label precision recall f1-score support
Army_mobilization 1.00 1.00 1.00 11
Closures/lockdown 0.71 0.86 0.77 84
Government_oversight 1.00 0.67 0.80 3
Restrictions_of_daily_liberties 0.72 0.73 0.73 75
Restrictions_of_fundamental_rights_and_civil_liberties 0.65 0.66 0.65 47
State_of_Emergency 0.81 0.74 0.77 53
Suspension_of_international_cooperation_and_commitments 1.00 0.33 0.50 6
micro-avg 0.73 0.76 0.75 279
macro-avg 0.84 0.71 0.75 279
weighted-avg 0.74 0.76 0.74 279
samples-avg 0.75 0.80 0.74 279