| |
Task 15: TempEval Temporal Relation Identification
Organized by
- James Pustejovsky, Department of Computer Science, Brandeis University
- Robert Gaizauskas, Department of Computer Science, University of Sheffield
- Mark Hepple, Department of Computer Science, University of Sheffield
- Graham Katz, Institute for Cognitive Science, University of Osnabrück
- Frank Schilder, Research & Development, Thomson Legal & Regulatory
- Marc Verhagen, Department of Computer Science, Brandeis University
Short Task Description
We specify three separate tasks that involve identifying event-time
and event-event temporal relations. A restricted set of temporal
relations will be used, which includes only the relations: BEFORE,
AFTER, and OVERLAP (defined to encompass all cases where event intervals
have non-empty overlap).
| TASK A:
| For a restricted set of event terms, identify temporal relations
between events and all time expressions appearing in the same
sentence. (NOTE: The restricted set of event terms is to
be specified by providing a list of root forms. Time expressions
will be annotated in the source, in accordance with TIMEX3.)
|
| TASK B:
| For a restricted set of event terms, identify temporal relations
between events and the Document Creation Time (DCT).
(NOTE: The restricted set of events will be the same as for Task
A. DCTs will be explicitly annotated in the source.)
|
| TASK C:
| Identify the temporal relations betweeen contiguous pairs of
matrix verbs. (NOTE: matrix verbs, i.e. the main verb of
the matrix clause in each sentence, will be explicitly annotated
in the source.)
|
Long Task Description
Newspaper texts, narratives and other such texts describe events
which occur in time and specify the temporal location and order of
these events. Text comprehension, even at the most general level,
involves the capability to identify the events described in a text and
locate these in time. This capablity is crucial to a wide range of NLP
applications, from document summarization and question answering to
machine translation. Furthermore, recent work on the annotation of
event and temporal relations have resulted in both a de-facto standard
for expressing these relations (TimeML) and a hand-built gold
standard of annotated texts (TimeBank). These
have already been used as the basis for automatic Time and Event
annotation tasks in a number of research projects in recent years.
As in many areas of NLP an open evaluation challenge in the area of
temporal annotation will serve to drive research forward. The
automatic identification of all temporal referring expressions, events
and temporal relations within a text is the ultimate aim of research
in this area. However, addressing this aim in a first evaluation
challenge is likely to be too difficult and a staged approach more
effective. Thus we here propose an initial evaluation exercise based
on three limited tasks that we believe are realistic both from the
perspective of assembling resources for development and testing and
from the perspective of developing systems capable of addressing the
tasks.
Task Definitions
Given a set of test texts (DataSet1) for which (1) sentence boundaries are annotated,
(2) all temporal expressions are annotated in accordance with TIMEX3, (3) the document
creation time (DCT) is specially annotated, and (4) a list of root forms of event
identifying terms (the Event Target List or ETL) is supplied,
complete the following tasks
- Task A: For each event whose root form occurs in the ETL, link
this event to time expressions in the same sentence as appropriate
using a restricted set of temporal relations
- Task B: For each event whose root form occurs in the ETL, link
this event to the DCT as appropriate using a restricted set of
temporal relations
- Task C: For each contiguous pair of matrix verbs link the
events signalled by these verbs as appropriate using a restricted set
of temporal relations. For task C a separate set of test texts
(DataSet2) is supplied which is annotated as is DataSet1, and in
addition is annotated to identify the main verb in the matrix clause
("matrix verb") of each sentence.
Remarks:
- The restricted set of temporal
relations contains: BEFORE, AFTER, and OVERLAP (defined to encompass
all cases where event intervals have non-empty overlap). In addition, we allow three disjunctive relations: BEFORE-OR-OVERLAP, OVERLAP-OR-AFTER and
VAGUE (for completely underspecified relations).
- By "as appropriate" here is meant as indicated in the
TimeML standard.
- For tasks A and B, in cases where there are multiple time
expressions in the sentence, the event should be linked to all TIMEXs
where appropriate.
- For the ETL we propose to use those terms whose variants in all
inflected forms occur as events in TimeBank 20 times or more, which
yields a list of around 63 root forms whose variants are included.
- Task C is the most ambitious of the three tasks proposed, one
which we view as exploratory in nature. Given the challenges it
presents we would not expect all participants to attempt it.
Resources
Participants will be supplied with a version of TimeBank (183
documents, approx. 2500 sentences) which has had TimeML annotations
removed or modified so they contain only the information to be supplied
in the test corpus plus the TLINK annotations to be found as part of
the task definitions.
The test corpus will consist of a number of articles not currently
included within TimeBank, which will be annotated in accordance with
the schemes outlined above. For tasks A and B, it is intended that
this should include at least 5 occurrences for each item in the
ETL. For task C, we propose to annotate around 20-25 news articles
(including of the order of 200-250 sentences) drawn from sources
similar to those used for TimeBank.
Evaluation Methodology
Tasks A, B and C can all be seen as classification tasks, where a
given temporal links is assigned a relation type from the set
BEFORE, AFTER, OVERLAP, BEFORE-OR-OVERLAP,
OVERLAP-OR-AFTER or
VAGUE. Precision and recall over these relation types are used as
evaluation metrics.
|