# Italian Legal Named Entity Recognition (NER)
ELECTRA-based model trained to extract entities of interest from Italian civil judgments issued by the Corte Suprema di Cassazione.

## Dataset
The model has been fine-tuned on 9000 judgments from 2016 to 2021 (1500 per year), labeled with a combination of rule-based and manual approaches.
It can be used to extract the following named entities from the text.

| Tag | Italian name | English name |
|:----|:-------------|:-------------|
| RIC | ricorso | appeal |
| RCR | ricorrente | petitioner |
| CTR | controricorrente | respondent |
| AVV | avvocato | lawyer |
| CNS | consigliere | counselor |
| PMI | pubblico ministero | prosecutor |
| DOM | domicilio | domicile |
| CDA | corte d’appello | appeal court |
| SNT | sentenza | judgment|



{"language": ["it"], "tags": ["legal"], "widget": [{"text": "la seguente SENTENZA sul ricorso 24817-2015 proposto da: ANDREA FORMISANO, elettivamente domiciliato in ROMA VIA S. TOMMASO D'AQUINO 7, presso lo studio dell'avvocato CARLO BORELLO, che lo rappresenta e difende giusta delega in calce; - ricorrente - contro SOGET SPA, CAMERA DI COMMERCIO DI PESCARA; - intimati - avverso la sentenza n. 169/2012 della COMM.TRIB.REG.SEZ.DIST. di PESCARA, depositata il 13/03/2012; udita la relazione della causa svolta nella pubblica udienza del 04/04/2018 dal Consigliere Dott. MILENA BALSAMO; udito il P.M. in persona del Sostituto Procuratore Generale Dott. GIOVANNI GIACALONE che ha concluso per l'inammissibilit\u00e0 in subordine rigetto del ricorso.", "example_title": "Judgment example"}]}
transformers pytorch electra token-classification legal it autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #electra #token-classification #legal #it #autotrain_compatible #endpoints_compatible #has_space #region-us 

Italian Legal Named Entity Recognition (NER)
============================================


ELECTRA-based model trained to extract entities of interest from Italian civil judgments issued by the Corte Suprema di Cassazione.


Dataset
-------


The model has been fine-tuned on 9000 judgments from 2016 to 2021 (1500 per year), labeled with a combination of rule-based and manual approaches.
It can be used to extract the following named entities from the text.




TAGS
#transformers #pytorch #electra #token-classification #legal #it #autotrain_compatible #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #electra #token-classification #legal #it #autotrain_compatible #endpoints_compatible #has_space #region-us 
