You are annotating data for an AI system that extracts events from news text.
An event consists of:
Trigger labels:
B-ATTACK beginning of attack triggerI-ATTACK continuation of triggerO not part of a triggerArgument labels:
B-AGENT / I-AGENT who carried out the attackB-TARGET / I-TARGET who/what was attackedB-PLACE / I-PLACE where it happenedWhich of the following could be valid attack triggers? (Check all that apply.)
Which word(s) did you choose as the event trigger? Why?
Is the trigger:
Does this sentence contain an ATTACK event?
Which argument roles were hardest to decide?
Looking back at your annotations in Parts 2–5, consider where other annotators might make different choices.
Where do you think annotators would disagree most?
Which guideline change would most improve agreement?
Why is event extraction harder than sequence labeling tasks like NER? (Check all that apply.)
Aspectual words describe the beginning, continuation, or end of an event, rather than the event itself.
Common aspectual words: began, started, continued, stopped, resumed, ended
Whether these should be included as part of an event trigger is often unclear and guideline-dependent.
Which word(s) did you label as the ATTACK trigger?
What does "began" contribute to the meaning of the event?
Does this sentence describe:
Should aspectual words like began, continued, ended be:
What guideline rule would reduce disagreement the most?
Which sentence(s) contain an ATTACK event?
What is the key difference between these sentences?
How many ATTACK events are described here?
Which rule would you adopt for this project?
Suppose you include began, continued, stopped as part of ATTACK triggers. Which outcomes are likely? (Check all that apply.)
If instead you exclude aspectual words from triggers, what might the model fail to learn?