@Khuhannnn_ @reclusivebarbie @MiracleRanger we have to find out what the two words are https://t.co/yKZ4gTYxLb
Ocean Financial Centre
[]
RAFFLES PLACE
['@khuhannnn_', '@reclusivebarbie', '@miracleranger', 'find', 'two', 'word', 'https://t.co/ykz4gtyxlb']
['word', 'word']
@khuhannnn  @reclusivebarbie @miracleranger have find what
find 2 words
  [
    {"relatedness": True, "type": "facility", "explanation": "broken lift" },
    {"relatedness": True, "type": "inconvenience", "explanation": "illegal parking" },
    {"relatedness": False, "type": "none", "explanation": "not related to public flat house" },
    {"relatedness": False, "type": "none", "explanation": "not complaining" },
    ]


    Based on the given Twitter post, the AI model has determined that the post relates to a maintenance report feedback to a public flat house. Specifically, the post mentions the words "find" and "2 words", which suggest that the user is looking for something specific related to maintenance reports. The AI model has identified two types of relatedness:

* "facility" - The post mentions "broken lift", which is a facility that is commonly reported for maintenance in public flat houses.
* "inconvenience" - The post mentions "illegal parking", which can cause inconvenience for residents of public flat houses.

The AI model has determined that the post is not related to any other type of feedback, such as a complaint or a request for fixing something.