# Clause type classification

We would like identify similar text (clauses) on a contract based on a trained corpus.

For instance:

Contract - small sample

NOW, THEREFORE, the parties hereto mutually agree as follows:

1. Scope of Services. The CONTRACTOR shall, in a proper and satisfactory manner as determined by OHA, provide all the goods and services set forth in Attachment – S1,
which is hereby made a part of this Contract.

2. Time of Performance. The performance required of the CONTRACTOR under this Contract shall be completed in accordance with the Time Schedule set forth in Attachment – S2, which is hereby made a part of this Contract.

3. Compensation. The CONTRACTOR shall be compensated according to the Compensation provision set forth in Attachment – S3, which is hereby made a part of this Contract.

4. Standards of Conduct Declaration. The Standards of Conduct Declaration of the CONTRACTOR is attached and is made a part of this Contract.


Trained clauses

We already have classified a few clauses from previous contracts. For instance:

#time_of_performance =
[
"Under this contract the performance required to be completed in accordance with the a predefined schedule."
,
"The completion of each phase of the project will be used to define the performance of this contract"
,
etc.
]


Where #time_of_performance is the classification for these clauses.

Expected result

Given the contract and the trained set, we would like to get parts/ranges of the texts and its classifications:

#time_of_performance = ["2. Time of Performance. The performance required of the CONTRACTOR under this Contract shall be completed in accordance with the Time Schedule set forth in Attachment – S2, which is hereby made a part of this Contract."]


Is there a known approach for this problem or a recommended processing pipeline?