Edit on GitHub
  • John Snow Labs
  • Aug 09, 2022

Augment Tickers with NASDAQ database

  • en
  • finance
  • companies
  • tickers
  • nasdaq
  • licensed

Description

This model allows you to, given a Ticker, get information about that company, including the Company Name, the Industry and the Sector.

Predicted Entities

Live Demo Copy S3 URI

How to use


document_assembler = nlp.DocumentAssembler()\
      .setInputCol('text')\
      .setOutputCol('document')

tokenizer = nlp.Tokenizer()\
      .setInputCols("document")\
      .setOutputCol("token")

tokenClassifier = nlp.RoBertaForTokenClassification.pretrained("finner_roberta_ticker", "en", "finance/models")\
  .setInputCols(["document",'token'])\
  .setOutputCol("ner")

ner_converter = nlp.NerConverter()\
      .setInputCols(["document", "token", "ner"])\
      .setOutputCol("ner_chunk")

CM = finance.ChunkMapperModel()\
      .pretrained('finmapper_nasdaq_companyname', 'en', 'finance/models')\
      .setInputCols(["ner_chunk"])\
      .setOutputCol("mappings")\
      .setRel('company_name')

pipeline = Pipeline().setStages([document_assembler,
                                 tokenizer, 
                                 tokenClassifier,
                                 ner_converter,  
                                 CM])

text = ["""There are some serious purchases and sales of AMZN stock today."""]

test_data = spark.createDataFrame([text]).toDF("text")

model = pipeline.fit(test_data)
res= model.transform(test_data)

res.select('mappings').collect()

Results

[Row(mappings=[Row(annotatorType='labeled_dependency', begin=46, end=49, result='AMZN', metadata={'sentence': '0', 'chunk': '0', 'entity': 'AMZN', 'relation': 'ticker', 'all_relations': ''}, embeddings=[]), Row(annotatorType='labeled_dependency', begin=46, end=49, result='Amazon.com Inc.', metadata={'sentence': '0', 'chunk': '0', 'entity': 'AMZN', 'relation': 'company_name', 'all_relations': ''}, embeddings=[]), Row(annotatorType='labeled_dependency', begin=46, end=49, result='Amazon.com', metadata={'sentence': '0', 'chunk': '0', 'entity': 'AMZN', 'relation': 'short_name', 'all_relations': ''}, embeddings=[]), Row(annotatorType='labeled_dependency', begin=46, end=49, result='Retail - Apparel & Specialty', metadata={'sentence': '0', 'chunk': '0', 'entity': 'AMZN', 'relation': 'industry', 'all_relations': ''}, embeddings=[]), Row(annotatorType='labeled_dependency', begin=46, end=49, result='Consumer Cyclical', metadata={'sentence': '0', 'chunk': '0', 'entity': 'AMZN', 'relation': 'sector', 'all_relations': ''}, embeddings=[]), Row(annotatorType='labeled_dependency', begin=57, end=61, result='NONE', metadata={'sentence': '0', 'chunk': '1', 'entity': 'today'}, embeddings=[])])]

Model Information

Model Name: finmapper_nasdaq_ticker
Type: finance
Compatibility: Finance NLP 1.0.0+
License: Licensed
Edition: Official
Input Labels: [ner_chunk]
Output Labels: [mappings]
Language: en
Size: 210.3 KB

References

https://data.world/johnsnowlabs/list-of-companies-in-nasdaq-exchanges