Update annotations for Iman/paper_17.txt

annotations/Iman/paper_17.txt.json

@@ -30,5 +30,13 @@
     "label": "Unsupported claim",
     "user": "Iman",
     "text": "DEGREE "
+  },
+  {
+    "file": "paper_17.txt",
+    "start": 1649,
+    "end": 2259,
+    "label": "Lacks synthesis",
+    "user": "Iman",
+    "text": " It has been a rising interest in event extraction under less data scenario. Liu et al. (2020) uses a machine reading comprehension formulation to conduct event extraction in a low-resource regime. Text2Event (Lu et al., 2021), a sequence-to-structure generation paradigm, first presents events in a linearized format, and then trains a generative model to generate the linearized event sequence. Text2Event's unnatural output format hinders the model from fully leveraging pre-trained knowledge. Hence, their model falls short on the cases with only extremely low data being available (as shown in Section 3)."
   }
 ]