Information extraction¶
Information Extraction (IE) tasks employ a wide array of data structures. We support the following, all of which can be
imported from metametric.structures.ie:
Mention: A span of text, defined by its starting and ending indices (inclusive or exclusive) in a passage of text.Relation: A typed binary relation between twoMentions.RelationSet: A collection ofRelations.Trigger: A typed, event-denotingMention.Argument: A typed, entity-denotingMentionthat satisfies a certainrolein an event.Entity: An entity, represented as a collection ofMentions that refer to it.EntitySet: A collection ofEntitys.Membership: A membership relation between a particularMentionand theEntityit refers to.Event: A complete event, represented by a particularTriggertogether with all of itsArguments.EventSet: A collection ofEvents.
One can define a wide array of metrics based on these data structures.
Coreference Resolution¶
We support three of the most widely used metrics for coreference resolution, including
\(\text{MUC}\) (muc; paper),
\(B^3\) [b_cubed_precision, b_cubed_recall; paper)
and \(\text{CEAF}_{\phi_4}\) (ceaf_phi4; paper), as well as a metric
suite (coref_suite) that includes all of these, plus the commonly reported average of all three. These metrics can be
imported from metametric.metrics.coref.