--A rule based approach by Hui Guo (a PhD student at NCSU) converted this to Python.
A Python class that extracts commitments from text using a list of rules.
A commitment is normative relation between a subject and an object in which the subject is committed to the object to bring about a consequent if the anticident holds. The following is an example commitment:
If you agree to the list, I'll go ahead and submit them.
- subject: I
- object: you
- anticident: you agree to the list
- consequent: go ahead and submit them
However, in everyday conversations, the object and the anticident are frequently ommitted. This class identifies the commitment in a sentence, and its subject and consequent only. The subject has to include I or we.
Note that sometimes people include compositions in their commitments. The example above actually includes two consequents: go head and submit them (well, whether or not they are actually two separate things is a differnt matter). This class also identifies the position of a composition: in the subject, in the consequent, or other places.
This Python code requires spacy and its models to parse texts. We recommend
the en_web_core_lg model.
This class checks whether or not a verb phrase is a consequent by checking whether the verb is commisive. We have included
a list of commisive verbs under the words folder. Please pay attention to the file path.
The verb be can be either commisive or not commisive. For example:
I'll be eight tomorrow.
I'll be there tomorrow.
Whether or not it is commisive depends on the word after it. We have included a list of be phrases under the words folder.
Please check our example code to see how to use it.
The following is a sample output.
[{
'para_id': 0,
'words': "If you agree to the list , I 'll go ahead and submit them .",
'rule': 'Rule 1: MD+V',
'subject': 'I',
'subject_id': [7],
'commisive': True,
'commisive_word': 'go',
'commisive_word_id': 9,
'compositions': [{'composition_type': 'Consequent',
'composition_word': 'and',
'composition_word_id': 11,
'compositioned_commisive_word': 'submit',
'compositioned_commisive_word_id': 12}]
},
{
'para_id': 1,
'words': "I 'll be eight tomorrow .",
'commisive': False
},
{
'para_id': 2,
'words': "I 'll be there tomorrow .",
'rule': 'Rule 1a: MD+be+other',
'subject': 'I',
'subject_id': [0],
'commisive': True,
'commisive_word': 'be there',
'commisive_word_id': 3,
'compositions': [],
}]
Please cite
@inproceedings{Kalia+SCC+2013,
author = {Anup K. Kalia and Hamid R. Motahari Nezhad and Claudio Bartolini and Munindar P. Singh},
title = {Monitoring Commitments in People-Driven Service Engagements},
booktitle = {Proceedings of IEEE International Conference on Services Computing},
pages = {160--167},
publisher = {{IEEE} Computer Society},
year = {2013},
address = {Santa Clara, US}
}