Currently, events are generated from labels purely using the granularity of those labels, i.e., whether a label is associated with (a property) of an event, or not. Consider the following sentence fragment:
Where it is impractical to substantially eliminate or reduce the hazard [...]
The current resolution algorithm will consider full labels and hence construct the two events [it].(is impractical to substantially eliminate) and [it].(reduce the hazard), while they should actually look as follows:
| Event |
Resolution in v1.0.0 |
NLP-improved resolution |
| 1 |
[it].(is impractical to substantially eliminate) |
[it].(is impractical to substantially eliminate the hazard) |
| 2 |
[it].(reduce the hazard) |
[it].(is impractical to substantially reduce the hazard) |
This can be achieved by analyzing the syntax tree of the sentence and resolving events with consideration of their grammatical dependencies. This however also introduces the need for resolving potential ambiguities (like coordination ambiguities in the aforementioned fragment: does "substantially" refer only to "eliminate" or also to "reduce"?).
Currently, events are generated from labels purely using the granularity of those labels, i.e., whether a label is associated with (a property) of an event, or not. Consider the following sentence fragment:
The current resolution algorithm will consider full labels and hence construct the two events [it].(is impractical to substantially eliminate) and [it].(reduce the hazard), while they should actually look as follows:
This can be achieved by analyzing the syntax tree of the sentence and resolving events with consideration of their grammatical dependencies. This however also introduces the need for resolving potential ambiguities (like coordination ambiguities in the aforementioned fragment: does "substantially" refer only to "eliminate" or also to "reduce"?).