Clarify annotated beliefs in dataset introduction

README.md

@@ -28,11 +28,11 @@ tags:
 
 # OmniToM
 
-OmniToM is a benchmark for evaluating Theory of Mind in language models through explicit belief-structure modeling. Many benchmarks ask a model to answer a question about a social story. OmniToM also records the beliefs behind that answer, so researchers can inspect what the model thinks each person knows, believes, or misunderstands.
+OmniToM is a benchmark for evaluating Theory of Mind in language models through explicit belief-structure modeling. Many benchmarks ask a model to answer a question about a social story. OmniToM provides annotated belief structures for the stories, so researchers can compare a model's extracted beliefs with what the benchmark records about each person.
 
 Each example pairs a short English story with actor-centered belief statements and seven labels for each belief. The benchmark supports two linked tasks:
 
-1. **Belief extraction:** Given a story, identify the actors and their belief statements.
+1. **Belief extraction:** Given a story, identify the actors, their belief statements, and the order of each belief.
 2. **Belief labeling:** Given a story and its belief statements, assign the seven schema labels to each belief.
 
 The released data contains the annotated stories and beliefs. The [paper](https://arxiv.org/abs/2605.26322) explains the benchmark design and evaluation protocol.