NER is good for really simple things (like getting names, addresses, etc.).
A lot of the use cases that we see, like extracting data from nested tables in 100-page-long private credit documents or flagging transactions and emails that contain a specific compliance violation, are impossible to do with NER.
NER is good for really simple things (like getting names, addresses, etc.).
A lot of the use cases that we see, like extracting data from nested tables in 100-page-long private credit documents or flagging transactions and emails that contain a specific compliance violation, are impossible to do with NER.
With Trellis, the idea is taht you can write any mappings and transformations (no matter how complex the tasks or the source data are).
A lot of the use cases that we see, like extracting data from nested tables in 100-page-long private credit documents or flagging transactions and emails that contain a specific compliance violation, are impossible to do with NER.
NER is good for really simple things (like getting names, addresses, etc.).
A lot of the use cases that we see, like extracting data from nested tables in 100-page-long private credit documents or flagging transactions and emails that contain a specific compliance violation, are impossible to do with NER.
With Trellis, the idea is taht you can write any mappings and transformations (no matter how complex the tasks or the source data are).