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| |
| def get_prompts_emea(): |
| system_prompt = '''An entity is a person(name), age, gender, title, named organization, city, state, country, address, zipcode, dates, site_ids, subject id, email, phone number, height, weight, Race, ethnicity, smoking habits, drinking habits, non-particiant, Social Security Number, Account Number, Medical Record Number, Medical History, Health Insurance Beneficiary Number, Certificate License Number, IP Address, Website URL, Vehicle Identifier. |
| All entities should strictly get extracted, but don't extract incorrect entities. |
| Entity present in any part of the paragraph should be detected. |
| Names/Person : Names of persons mentioned in the input sentence or paragraph.ile |
| Age: Age of a person should get detected. Some examples are 12 yo, 15 years old, 11 months old, 79 years, 51 yrs, 18-year-old, > 13 Years, <14 years |
| Date: All dates should get detected as Dates. Some examples are 10-1-2021, 23-01-2022, 27th June, June 29, 10-09-2007, 4/5/67, 7/67, 31-12-2000. start_date, end_date should get detected as Date itself. |
| Gender: Consider instances of "Male," "Female," "male," "female," "She," "He," "women," and "man" as gender references, note don't extract other than these instances |
| Study_day: Day 2, Day 5, day 9, day 11 of study, 3rd day of study, etc., |
| Height: six feet tall, 5 feet 7 inches, 8 feet 1 inch, 170 centimeters tall, 188 centimeters, 189cm, 140.73 cm, etc., should be detected as Height. |
| Weight: some of the examples are 100 pounds, 50 pounds, 77.4 pounds, 66 kgs, 78.9 kilograms, 88 kilograms, etc.,should be detected as Weight. |
| Race: some of the examples of Race are caucasian, Asian, Black, White, African Amercian, Hispanic descent, mixed race heritage, Native American, etc., should be detected as Race. |
| Phone_number: persons contact number or phone number should get detected. example format of phone numbers are +91443563223, (123)456-7890, +1(123)456-7890, (555) 123-4567, +44 20 1234 5678 |
| Email: all emails from the paragraph should be detected. |
| Site_id: Site ID #56, Site ID 87, siteid #22, siteid356, at Site Y789, at site 235 etc., |
| Address: Extract Address from paragraph and should detect as Address. |
| Country: Extract Country names from paragraph. |
| Non_participant: non-participant, observer, spectator etc., extract these type of entities |
| Smoking_habit: never smoked, smoker, non-smoker etc., extract these type of entities |
| Drinking_habit: never drinked, drinker, drinking, non-drinker etc., extract these type of entities |
| BMI: Body Mass Index value should get detected. |
| Social Security Number: Social Security Number should get detected from paragraph. |
| Medical Record Number: All Medical Record Numbers should get detected from paragraph. |
| If there are multiple values for same entity they should be extracted with | separation. |
| Random text should not get detected as any of above entities. |
| All entities from above should strictly be extracted. |
| URLs shouldn't get detected as Location or Address. |
| ''' |
|
|
| example1 = '''Essentially , Mr. Cornea is a 60 year old male who noted the onset of dark urine during early January . |
| Answer: |
| Name: Mr. Cornea |
| Age: 60 year old |
| Gender: male |
| Date: early January |
| End-Answer |
| ''' |
|
|
| example2 = '''In the 205 subjects with post-ofatumumab HAHA results (G2 MSD ECL assay; Section 3.5), one subject (Subject 257) tested positive for HAHA on 10-1-2021, 23-01-2022, and 185 subjects had all negative post-ofatumumab HAHA results with at least one ofatumumab plasma concentration low enough (<200 µg/mL) for the negative HAHA results to be considered conclusive. Subject 257 tested positive for HAHA at the six-month follow-up visit (titer = 16); samples at all other time points were negative. |
| 2 patients were released from the study due to inactivity. |
| Answer: |
| Subject_id: 257 | 257 |
| Date: 10-1-2021 | 23-01-2022 |
| Numper_of_patients: 2 | 205 | 185 |
| End-Answer |
| ''' |
| example3 = '''Subject 169: 54 years, Female, Pneumocystis jirovecii pneumonia, 61 days after last dose, resolved. The subject(CS3A Subject 1833-2303) was hospitalized for severe bronchopneumonia. Bronchoalveolar lavage and polymerase chain reaction (PCR) for Pneumocystis were positive for Pneumocystis jiroveci. She was hospitalized on 27th June and discharged on June 29. Two patients were on the study from 10-09-2007. |
| Answer: |
| Subject_id: 169 | 1833-2303 |
| Age: 54 years |
| Gender: Female | She |
| Race: White |
| Date: 27th June | June 29 | 10-09-2007 |
| Medical_history: Pneumocystis jirovecii pneumonia |
| End-Answer |
| ''' |
|
|
| example4 = '''Saw Dr Oakley 4/5/67 - he was happy with results of ETT at Clarkfield. To f/u 7/67. No CP's since last admit. On Day 521, the patient was discharged. |
| Another patient died of cardio-respiratory arrest on Day 8. |
| Answer: |
| Name: Dr Oakley |
| Date: 4/5/67 | 7/67 |
| Gender: he |
| Location: Clarkfield |
| Study_day: Day 521 | Day 8 |
| End-Answer |
| ''' |
|
|
| example5 = '''Patient 12367/2134 Oseltamivir 100 mg IV q12h for 5 days S295H/Y Patient 12367/2144 was a 57 year old male enrolled on 31-12-2000, on Day 5(03-Jan-2021) the patient was admitted. |
| Answer: |
| Patient_id: 12367/2134 | 12367/2144 |
| Gender: male |
| Date: 31-12-2000 | 03-Jan-2021 |
| Study_day: Day 5 |
| Age: 57 year old |
| End-Answer''' |
|
|
| example6 = '''Final Clinical Study Report - NV25118: A Randomized, Multicenter, Single Blinded, Parallel Study of the Safety of 100 mg and 200 mg Oseltamivir Administered Intravenously for the Treatment of Influenza in Patients Aged > 13 Years. Report No. 1037027. June 3, 2013 |
| Answer: |
| Study_id: NV25118 |
| Age: 13 Years |
| Date: June 3, 2013 |
| End-Answer''' |
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| example7 = '''The medical history included throat cancer beginning in 2011 and ending in 2011, a broken hip beginning in 2011 and ending in 2011, insertion of two stents in 2012, coronary artery bypass surgery on 25-Jun-2014, a right cerebrovascular accident on 25-Jun-2014, aortic valve replacement on 25-Jun-2014, bilateral cataracts on 15-Aug-2014. |
| Answer: |
| Medical_history: throat cancer | broken hip | insertion of two stents | coronary artery bypass surgery | right cerebrovascular accident | aortic valve replacement | bilateral cataracts. |
| Date: 25-Jun-2014 | 25-Jun-2014 | 25-Jun-2014 | 15-Aug-2014 |
| End-Answer''' |
|
|
| example8 = '''1083\nPatient [AUS02T-0215-787043] - Death\n(disseminated intravascular coagulation),\nSAE (haemorrhage intracranial,\ndisseminated intravascular coagulation) . |
| Answer: |
| Subject_id: [AUS02T-0215-787043] |
| End-Answer''' |
|
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|
| example9 = '''The accident involved Vehicle ID: ABC123 and occurred on August 15, 2023. |
| Answer: |
| Vehicle_Identifier: ABC123 |
| Date: August 15, 2023 |
| End-Answer |
| ''' |
| example10 = '''Sarah underwent an ECHO and endoscopy at Ingree and Ot of Weamanshy Medical Center(www.wmchospital.com) on April 28 . In one patient the SAE had a fatal\noutcome. |
| Answer: |
| Name: Sarah |
| Location: Weamanshy Medical Center |
| URL: www.wmchospital.com |
| Date: April 28 |
| End-Answer''' |
|
|
| example11 = '''The patient had never smoked and was a former drinker. The subject was accompanied by his mother. He then completed study treatment with a total of 19 doses of IV oseltamivir (10 doses standard treatment plus 9 doses of treatment extension). |
| Answer: |
| Smoking_habit: never smoked |
| Drinking_habit: former drinker |
| Gender: his | He |
| Non_participant: mother |
| End-Answer''' |
|
|
| example12 = '''Patient ois/51317-31580/10653 was a 54-year-old Hispanic male. he doesn't have anything to inform. He's good at writing, participated in a medical research study at Site Y789. |
| Answer: |
| Subject_id: ois/51317-31580/10653 |
| Age: 54-year-old |
| Race: Hispanic |
| Gender: male | he | He's |
| Site_id: Y789 |
| End-Answer''' |
| example13 = '''This Task Order CPDR001F2301 (“Task Order”) shall be binding upon the undersigned upon its execution by the duly authorized representative(s) of Novartis. ', 'It is subject to the terms of that certain General Services Agreement (GSA) between Novartis Pharmaceuticals Corporation, with an office at 59 Route 10, East Hanover, NJ 07936 and Statistics Collaborative Inc. (“SCI” or “Organization”), with an office at 1625 Massachusetts Avenue NW, Suite 600, Washington, DC 20036 dated 16 June 2016 (“Agreement”). |
| Answer: |
| Address: 59 Route 10, East Hanover, NJ 07936 | 1625 Massachusetts Avenue NW, Suite 600, Washington, DC 20036 |
| Date: 16 June 2016 |
| End-Answer''' |
|
|
| example14 = '''ATC classes are presented alphabetically; preferred terms are sorted within ATC class alphabetically. - A medication can appear with more than one ATC class. Program: CIGG013A/CIGG013A1101J/report/pgm_saf/t_cmd03.sas, 18:33 14OCT2014 Final. https://www.google.com/ |
| Study_dates: 18 Nov 2009-28 Jun 2010 |
| Answer: |
| Program: CIGG013A/CIGG013A1101J/report/pgm_saf/t_cmd03.sas |
| Date: 14OCT2014 | 18 Nov 2009 | 28 Jun 2010 |
| URL: https://www.google.com/ |
| End-Answer |
| ''' |
| example15 = '''This Task Order CPDRB0081E5 (“Task Order”) shall be binding upon the undersigned upon its execution by the duly authorized representative(s) of Novartis. It is subject to the terms of that certain General Services Agreement (GSA) between Novartis Pharmaceuticals Corporation, with an office at 59 Route 10, East Hanover, NJ 07936 and Acme Inc. (“Organization”), with an office at 123 Ben Avenue NW, Suite 600, Washington, DC 20001 dated 16 June 2016 (“Agreement”). |
| Answer: |
| Address: 59 Route 10, East Hanover, NJ 07936 | 123 Ben Avenue NW, Suite 600, Washington, DC 20001 |
| Date: 16 June 2016 |
| End-Answer |
| ''' |
| example16 ='''In a pre-clinical study day, Subject ID #235 with Medical Record Number 783-ABD has a BMI of 27.5. His name is John Doe, aged 35, residing at 123 Main St. He's a non-participant, non-smoker, and non-drinker. His medical history includes allergies. He's 6 feet tall, male, Caucasian, and his health insurance beneficiary number is 4567890. He doesn't have a social security number but has an account number 123456789. He drives a Toyota with license plate XYZ-123. contact him at john.doe@exam.com |
| Answer: |
| Subject_id: 235 |
| Medical_Record_Number: 783-ABD |
| BMI: 27.5 |
| Name: John Doe |
| Age: 35 |
| Address: 123 Main St. |
| Non_participant: non-participant |
| Smoking_habit: non-smoker |
| Drinking_habit: non-drinker |
| Medical_history: allergies |
| Height: 6 feet |
| Gender: male |
| Race: Caucasian |
| Health_Insurance_Beneficiary_Number: 4567890 |
| Account_Number: 123456789 |
| Vehicle_Identifier: Toyota | XYZ-123 |
| Email: john.doe@exam.com |
| End-Answer |
| ''' |
| example17 = '''He is a non-participant, non-smoker, and non-drinker. Anyone can reach at (555) 123-4567 |
| Answer: |
| Gender: He |
| Non_participant: non-participant |
| Smoking_habit: non-smoker |
| Drinking_habit: non-drinker |
| Phone_number:(555) 123-4567 |
| End-Answer |
| ''' |
| example18 = '''Dr. Sarah Miller has a valid medical license (Certificate License Number: MD12345) and practices at 789 Oak Avenue. her medical history includes allergies. |
| Answer: |
| Name: Dr. Sarah Miller |
| Certificate_License_Number: MD12345 |
| Adddress: 789 Oak Avenue |
| Gender: her |
| Medical_history: allergies |
| End-Answer |
| ''' |
| example19 = '''During a pre-clinical study day at Site ID 56, Subject ID 1234, a 40-year-old Caucasian female named Amritha, her bmi with 2.65. |
| Answer: |
| Site_id: 56 |
| Subject_id: 1234 |
| Age: 40-year-old |
| Race: Caucasian |
| Gender: female | her |
| Name: Amritha |
| BMI: 2.65 |
| End-Answer |
| ''' |
| example20 = '''John, a non-smoker and an occasional drinker, He importance of maintaining a healthy lifestyle. Sarah, his colleague, shares his commitment to wellness. Despite societal pressures, they prioritize their health by avoiding tobacco and moderating alcohol consumption. |
| Answer: |
| Name: John | Sarah |
| Drinking_habit: occasional drinker | alcohol consumption |
| Gender: He | his | his |
| Smoking_habit: non-smoker | tobacco |
| End-Answer |
| ''' |
| example21 = '''Study Dates: First patient screened: Jan 15, 2010 Last patient visit: Sept 14, 2012 |
| Answer: |
| Date: Jan 15, 2010 | Sept 14, 2012 |
| End-Answer |
| ''' |
| example22 = '''Father: Hypertension, deceased at 70 (myocardial infarction) Mother: Type 2 Diabetes Mellitus, alive, age 72 |
| Answer: |
| Medical_history: Hypertension | Diabetes Mellitus |
| Age: 70 | 72 |
| End-Answer |
| ''' |
|
|
| whole_task = '''Given the paragraph below identify list of possible entities. |
| Paragraph:''' |
|
|
| example_list = [example1,example17,example12,example11,example13,example14, example2, example9, example3, example4, example5, example6, example15, example7, example8, example9, example10,example16, example18,example19, example20, example21, example22 ] |
|
|
| final_prompt = '' |
| for ex in example_list: |
| final_prompt = final_prompt+''+whole_task+'\n' |
| final_prompt = final_prompt+''+ex+'\n' |
| |
| final_prompt = system_prompt+'\n'+final_prompt |
| return final_prompt, whole_task |
|
|
| def get_prompts_emea2(): |
| |
| |
| system_prompt2 = '''An entity is a Organization_name, Dosage Values, Drug names, Bank Account Numbers, Bank Swift Codes, Cost Values. |
| All entities should strictly get extracted, but don't extract incorrect entities. |
| Entity present in any part of the paragraph or sentence should be detected. |
| Dosages: Medical Dosage values should get detected. Some examples are 500 mg, 100 mg, 1000mg, 10ml, 250mg, 20mcg, 15μg, 19μg, 21 μg, 80 μg, 800 mcg, etc., |
| Drug_names : Drug names should get detected. Some examples are Adelphane-Esidrex, Afinitor, Amturnide, Anafranil, Arcapta Neohaler, Brinaldix, Clozaril, Co-Diovan, EXV8111, Fabhalta, FUB5231, JDQ443, KAE609, Kisqali, KLU1563 |
| Organization_names: Extract Organization names from given paragraph or sentence. |
| Account_Number: Bank Account Numbers should get detected. |
| Swift_code: Bank SWIFTcodes should get detected. |
| Costs: Only Costs Numerical monetory values like Euro(€),rupee(₹),doller($) should get detected as costs. Some examples are €10, €1200, €10,000, $100, $70,000, ₹25 |
| If there are multiple values for same entity they should be extracted with | separation. |
| Random text should not get detected as any of above entities. |
| All entities from above should strictly be extracted |
| ''' |
| |
| |
| example1 ='''The international conference registration fee is €300 for European attendees, ₹25,000 for participants from India, and $350 for delegates from other countries. Please note that all fees are exclusive of any applicable taxes or transaction fees. Payment can be made in the respective currencies via bank transfer or credit card. For currency conversion rates, please consult your financial institution or use a reliable online currency converter. Early bird discounts are available for registrations completed before the deadline. We look forward to welcoming you to the conference! |
| Answer: |
| Costs: €300 | ₹25,000 | $350 |
| End-Answer''' |
| example2 = '''The project budget for the construction of the new pharmaceutical manufacturing facility has been estimated at €10 million, with additional expenses projected in Indian rupees (INR) amounting to ₹50 crore. This budget includes the procurement of state-of-the-art equipment and machinery sourced from various suppliers worldwide, with an estimated cost of $12.5 million in US dollars. The allocation of funds across different currencies reflects the global nature of the project, ensuring that costs are managed efficiently to meet quality standards and regulatory requirements. |
| Answer: |
| Costs: €10 | ₹50 | $12.5 |
| End-Answer''' |
| example3 = '''She budgeted approximately $150 per night for accommodations, €50 for meals, and ₹1,500 for daily miscellaneous expenses. This comprehensive budget allowed her to comfortably experience the beauty of European countries while managing her day-to-day spending. |
| Answer: |
| Costs: $150 | €50 | ₹1,500 |
| End-Answer''' |
| example4 = '''Bank Name: ABC Bank Branch: XYZ Branch Account Holder: [Your Name] Account Number: 123-456-789 SWIFT Code: XYZABCD1234 IBAN: [Your IBAN Number] Routing Number: 987654321 |
| Answer: |
| Account_number: 123-456-789 |
| Swift_code: XYZABCD1234 |
| End-Answer''' |
| |
| example5 = '''Bank Name: DEF Bank Branch: PQR Branch Account Holder: [Your Name] Account Number: 9876543210 SWIFT Code: DEFPQR12345 IBAN: [Your IBAN Number] Routing Number: 123456789 |
| Answer: |
| Account_number: 9876543210 |
| Swift_code: DEFPQR12345 |
| End-Answer''' |
| example7 = '''Prescription Label: "Take 1 tablet by mouth daily with food." "Apply a thin layer of cream to the affected area twice daily." "Administer 10 mg/mL orally every 4 hours as needed for pain."Clinical Trial Protocol: "Participants will receive 100 mg of Drug A orally once daily for 12 weeks." "Patients will be administered 50 mg/kg of Drug B intravenously every 2 weeks for 6 cycles." "Dosage escalation will occur in 25 mg increments every week until a maximum tolerated dose is reached." |
| Answer: |
| Dosages: 1 tablet | 10 mg/ml | 100 mg | 50 mg/kg | 25 mg |
| End-Answer''' |
| example6 = '''Final Clinical Study Report - NV25118: A Randomized, Multicenter, Single Blinded, Parallel Study of the Safety of 100 mg and 200 mg Oseltamivir Administered Intravenously for the Treatment of Influenza in Patients Aged > 13 Years. Report No. 1037027. June 3, 2013 |
| Answer: |
| Dosages: 100 mg | 200 mg |
| Drug_names: Oseltamivir |
| End-Answer''' |
| |
| example8 = '''Medication Package Insert:"Recommended dosage for adults: 500μg to 1000μg orally every 6 hours, as needed." "Pediatric dosage: 10 mg/kg orally every 8 hours for children aged 2 to 12 years." "For elderly patients (>65 years), initiate therapy at 25% of the recommended adult dosage." Hospital Discharge Instructions: "Continue taking 75 μg of Medication C orally twice daily for 10 days.""Start with 250 mg of Medication D intravenously every 6 hours, then titrate to effect." "Resume home medications: 20 mg of Medication E orally once daily at bedtime." |
| Answer: |
| Dosages: 500μg | 1000μg | 10 mg/kg | 75 μg | 250 mg | 20 mg |
| End-Answer''' |
| |
| example9 = '''Acme Corporation, represented herein as Party A, hereby enters into a distribution agreement with Smith & Sons Enterprises, hereinafter referred to as Party B. Under the terms of this agreement, Party A agrees to supply Party B with pharmaceutical products manufactured at Novartis Pharma AG facility located in Switzerland. Party B, in turn, agrees to distribute and promote these products within the designated territories. This agreement also encompasses cooperation between Novartis Pharma Schweiz AG, a subsidiary of Novartis, and Party B for marketing activities in the Indian market. Both parties acknowledge and agree to abide by the terms and conditions outlined herein, including confidentiality provisions and dispute resolution mechanisms. |
| Answer: |
| Organization_names: Acme Corporation | Smith & Sons Enterprises| Novartis Pharma AG | Novartis Pharma Schweiz AG |
| End-Answer''' |
| example10 = '''This Research Collaboration Agreement ("Agreement") is entered into on [Date] by and between Novartis Institutes for BioMedical Research, Inc. ("Novartis"), a research organization duly organized and existing under the laws of [Country], having its principal place of business at [Address], and MedTech Innovations LLC ("MedTech"), a technology company duly organized and existing under the laws of [Country], having its principal place of business at [Address]. |
| Answer: |
| Organization_names: Novartis Institutes for BioMedical Research, Inc. | MedTech Innovations LLC. |
| End-Answer''' |
| example11 = '''This Task Order CPDR001F2301 (“Task Order”) shall be binding upon the undersigned upon its execution by the duly authorized representative(s) of Novartis. ', 'It is subject to the terms of that certain General Services Agreement (GSA) between Novartis Pharmaceuticals Corporation, with an office at 59 Route 10, East Hanover, NJ 07936 and Statistics Collaborative Inc. (“SCI” or “Organization”), with an office at 1625 Massachusetts Avenue NW, Suite 600, Washington, DC 20036 dated 16 June 2016 (“Agreement”).\n |
| Answer: |
| Organization_names: Novartis Pharmaceuticals Corporation | Statistics Collaborative Inc. |
| End-Answer''' |
| example12 = '''Afinitor, Arcapta Neohaler, and Clozaril are among the pharmaceuticals frequently prescribed for a variety of medical conditions. |
| Answer: |
| Drug_names: Afinitor | Arcapta Neohaler | Clozaril |
| End-Answer''' |
| example13 = '''Femara functions as a protease-activated receptor-1 (PAR-1) antagonist, effectively inhibiting platelet activation and reducing the risk of thrombotic events in patients with a history of myocardial infarction or peripheral arterial disease. With its unique mechanism of action and demonstrated efficacy in clinical trials, this drug offers new hope for patients seeking to mitigate the devastating consequences of atherosclerosis and other cardiovascular conditions. |
| Answer: |
| Drug_names: Femara |
| End-Answer |
| ''' |
| example14 = '''Coartem, Kisqali, and Leqvio are among the pharmaceuticals utilized in the treatment and management of diverse medical conditions. specific dosage regimen based on the patient's weight and age. 600 mg daily for 21 days, cutaneous injection at a dosage of 300 mg every six months after an initial loading dose. |
| Answer: |
| Drug_names: Coartem | Kisqali | Leqvio |
| Dosages: 600 mg | 300 mg |
| End-Answer |
| ''' |
| example15 = '''This Task Order CPDRB0081E5 (“Task Order”) shall be binding upon the undersigned upon its execution by the duly authorized representative(s) of Novartis. It is subject to the terms of that certain General Services Agreement (GSA) between Novartis Pharmaceuticals Corporation, with an office at 59 Route 10, East Hanover, NJ 07936 and Acme Inc. (“Organization”), with an office at 123 Ben Avenue NW, Suite 600, Washington, DC 20001 dated 16 June 2016 (“Agreement”). |
| Answer: |
| Orgnaization_names: Novartis Pharmaceuticals Corporation | Acme Inc |
| End-Answer |
| ''' |
| example16 = ''''Patient 25291/3280 Oseltamivir 100 mg IV q12h for 5 days H275H/Y Patient 25291/3280 was a 57 year old male enrolled on 16-09-2021 , 2 days after onset of influenza symptoms in the hospital. ', "The patient's medical history included congestive cardiac failure, cardiac murmur, aortic stenosis, aspiration pneumonia and acute respiratory failure. |
| Drug_names: Oseltamivir |
| Dosages: 100 mg |
| End-Answer |
| ''' |
| whole_task = '''Given the paragraph below identify list of entities that are mentioned in list [Person/Name, Dosages,]. |
| Paragraph:''' |
|
|
| example_list = [example1, example5, example3,example9, example4, example6, example13, example2, example7, example8, example10, example11, example12,example15,example14,example16] |
|
|
| final_prompt = '' |
| for ex in example_list: |
| final_prompt = final_prompt+''+whole_task+'\n' |
| final_prompt = final_prompt+''+ex+'\n' |
|
|
| final_prompt = system_prompt2+'\n'+final_prompt |
| return final_prompt,whole_task |
| |
