<commit_before>---
layout: model
title: Sentence Entity Resolver for CPT (``sbiobert_base_cased_mli`` embeddings)
author: <NAME>
name: sbiobertresolve_cpt
language: en
repository: clinical/models
date: 2020-11-27
tags: [clinical,entity_resolution,en]
article_header:
    type: cover
use_language_switcher: "Python-Scala-Java"
---

{:.h2_title}
## Description
This model maps extracted medical entities to CPT codes using chunk embeddings.

{:.h2_title}
## Predicted Entities 
CPT Codes and their normalized definition with ``sbiobert_base_cased_mli`` sentence embeddings.

{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
[Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}{:target="_blank"}
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_2.6.4_2.4_1606235767322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}

{:.h2_title}
## How to use 
<div class="tabs-box" markdown="1">

{% include programmingLanguageSelectScalaPython.html %}

```python
chunk2doc = Chunk2Doc().setInputCols("ner_chunk").setOutputCol("ner_chunk_doc")
<commit_msg>[skip_ci] new metadata lines added to 173.file 2020-11-27-sbiobertresolve_cpt_en.md<commit_after>---
layout: model
title: Sentence Entity Resolver for CPT (``sbiobert_base_cased_mli`` embeddings)
author: <NAME>
name: sbiobertresolve_cpt
language: en
repository: clinical/models
date: 2020-11-27
task: Entity Resolution
edition: Spark NLP for Healthcare 2.6.4
tags: [clinical,entity_resolution,en]
article_header:
    type: cover
use_language_switcher: "Python-Scala-Java"
---

{:.h2_title}
## Description
This model maps extracted medical entities to CPT codes using chunk embeddings.

{:.h2_title}
## Predicted Entities 
CPT Codes and their normalized definition with ``sbiobert_base_cased_mli`` sentence embeddings.

{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
[Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}{:target="_blank"}
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_2.6.4_2.4_1606235767322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}

{:.h2_title}
## How to use 
<div class="tabs-box" markdown="1">

{% include programmingLanguageSelectScalaPython.html %}

```python
chunk2doc = Chunk2Doc().setInputCols("ner_chunk").setOutputCol("ner_chunk_doc")

{'fraction_non_alphanumeric': 0.1305732484076433, 'fraction_numerical': 0.029723991507430998, 'mean_word_length': 6.766483516483516, 'pattern_counts': {'":': 0, '<': 11, '<?xml version=': 0, '>': 11, 'https://': 4, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '6073930', 'n_tokens_mistral': 1080, 'n_tokens_neox': 975, 'n_words': 170}