Spaces:
Build error
Build error
File size: 4,665 Bytes
c5e4524 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 |
import re
# Entity Extraction
def generate_alpaca_ner_prompt(query):
prompt = f"""Below is an instruction that describes a task, paired with an input that provides further context. Use the following guidelines to extract the entities representing the Company, Quarter, and Year in the sentence.
### Instruction:
- The output should be in the form "Company - Value, Quarter - Value, Year - Value".
- The output should be in the form "Company - None, Quarter - None, Year - None", if no entities are found.
- Only use entities that exist in the final sentence.
- If Company cannot be found in the sentence, return "none" for that entity.
- If Quarter cannot be found in the sentence, return "none" for that entity.
- If Year cannot be found in the sentence, return "none" for that entity.
- If there is ambiguity finding the entity, return "none" for that entity.
### Input:
What was discussed regarding Services revenue performance in Apple's Q3 2020 earnings call?
Company - Apple, Quarter - Q3, Year - 2020
How has the growth in Q1 been for the consumer market as seen by AMD?
Company - AMD, Quarter - Q1, Year - none
What was the long term view on GOOGL's cloud business growth as discussed in their earnings call?
Company - Google, Quarter - none, Year - none
What is Nvidia's outlook in the data center business in Q3 2020?
Company - Nvidia, Quarter - Q3, Year - 2020
What are the expansion plans of Amazon in the Asia Pacific region as discussed in their earnings call?
Company - Amazon, Quarter - none, Year - none
What did the Analysts ask about CSCO's cybersecurity business in the earnings call in 2016?
Company - Cisco, Quarter - none, Year - 2016
{query}
### Response:"""
return prompt
def format_entities_flan_alpaca(values):
"""
Extracts the text for each entity from the output generated by the
Flan-Alpaca model.
"""
try:
company_string, quarter_string, year_string = values.split(", ")
except:
company = None
quarter = None
year = None
try:
company = company_string.split(" - ")[1].lower()
company = None if company.lower() == "none" else company
except:
company = None
try:
quarter = quarter_string.split(" - ")[1]
quarter = None if quarter.lower() == "none" else quarter
except:
quarter = None
try:
year = year_string.split(" - ")[1]
year = None if year.lower() == "none" else year
except:
year = None
print((company, quarter, year))
return company, quarter, year
def extract_quarter_year(string):
# Extract year from string
year_match = re.search(r"\d{4}", string)
if year_match:
year = year_match.group()
else:
year = None
# Extract quarter from string
quarter_match = re.search(r"Q\d", string)
if quarter_match:
quarter = "Q" + quarter_match.group()[1]
else:
quarter = None
return quarter, year
def extract_ticker_spacy(query, model):
doc = model(query)
entities = {ent.label_: ent.text for ent in doc.ents}
print(entities.keys())
if "ORG" in entities.keys():
company = entities["ORG"].lower()
else:
company = None
return company
def clean_entities(company, quarter, year):
company_ticker_map = {
"apple": "AAPL",
"amd": "AMD",
"amazon": "AMZN",
"cisco": "CSCO",
"google": "GOOGL",
"microsoft": "MSFT",
"nvidia": "NVDA",
"asml": "ASML",
"intel": "INTC",
"micron": "MU",
}
ticker_choice = [
"AAPL",
"CSCO",
"MSFT",
"ASML",
"NVDA",
"GOOGL",
"MU",
"INTC",
"AMZN",
"AMD",
]
year_choice = ["2020", "2019", "2018", "2017", "2016", "All"]
quarter_choice = ["Q1", "Q2", "Q3", "Q4", "All"]
if company is not None:
if company in company_ticker_map.keys():
ticker = company_ticker_map[company]
ticker_index = ticker_choice.index(ticker)
else:
ticker_index = 0
else:
ticker_index = 0
if quarter is not None:
if quarter in quarter_choice:
quarter_index = quarter_choice.index(quarter)
else:
quarter_index = len(quarter_choice) - 1
else:
quarter_index = len(quarter_choice) - 1
if year is not None:
if year in year_choice:
year_index = year_choice.index(year)
else:
year_index = len(year_choice) - 1
else:
year_index = len(year_choice) - 1
return ticker_index, quarter_index, year_index
|