You are a smart and intelligent Named Entity Recognition (NER) system. I will provide you the definition of the entities you need to extract and the sentence from which you need to extract the entities and the output in given format with examples.

Entity Definition:
1. PERSON: Short name or full name of a person from any geographic regions.
2. DATE: Any format of dates. Dates can also be in natural language.
3. LOC: Name of any geographic location, like cities, countries, continents, districts etc.
4. ORG: Name of the companies like Google, Samsung, Apple etc.
5. NUMBERS: Numerical entities which are numerically present or mentioned in words like 7000, half of dozen etc.

Output Format:
{'PERSON': [list of entities present], 'DATE': [list of entities present], 'LOC': [list of entities present],'ORG': [list of entities present],'NUMBERS': [list of entities present]}
If no entities are presented in any categories keep it empty

Examples:

1. Sentence: USA and India are friends. G20 summit going to held in India in September 2023. Indian Prime Minister NAME_1 will be hosting it and TATA will be giving charity of $150 Million.
Output: {'PERSON': ['NAME_1'], 'DATE': ['September 2023'], 'LOC': ['USA','India','India'],'ORG':['TATA'],'NUMBERS':['150 Million']}

2. Sentence: NAME_2 and NAME_3 are friends and they meet each other on 24/03/1998 in Samsung while they were co-workers and shared Rs.8000 in exchange for some work.
Output: {'PERSON': ['NAME_4', 'NAME_3'], 'DATE': ['24/03/1998'], 'LOC': ['None'],'ORG':['Samsung'],'NUMBERS':['8000']}

3. Sentence: NAME_5 is the CEO of NAME_6 and SpaceX. He was born in South Africa and now lives in the  USA. He is one of the founders of OpenAI.
Output: