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snac.yml
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template_name: snac
template_label: SNaC
template_description: Coherence Error Detection for Narrative Summarization
# ========================================================================================
#
# The Goyal et al., 2022 paper annotates 3 different model sizes, which we randomly sample.
# for our demo data. For their vizualizer, see:
# https://coherence-annotation-summaries.herokuapp.com/explore_dataset
#
# ========================================================================================
interface_text:
typology:
source_label: "Article"
target_label: "Generated Summary"
disable:
- annotation
edits:
- name: CharE
label: "Character w/o Introduction"
color: blue
icon: fa-person-circle-question
enable_output: true
- name: RefE
label: "Missing Reference"
color: "#bd3dbf"
icon: fa-expand
enable_output: true
- name: SceneE
label: "Abruct Scene Transition"
color: teal
icon: fa-people-pulling
enable_output: true
- name: InconE
label: "Inconsistency"
color: yellow
icon: fa-triangle-exclamation
enable_output: true
- name: RepE
label: "Repetition"
color: orange
icon: fa-arrows-spin
enable_output: true
- name: GramE
label: "Ungrammatical or Nonsensical"
color: red
icon: fa-spell-check
enable_output: true
- name: CorefE
label: "Unclear Coreference"
color: green
icon: fa-people-arrows
enable_output: true
paper_link: https://aclanthology.org/2022.emnlp-main.29
citation: |
@inproceedings{goyal-etal-2022-snac,
title = "{SN}a{C}: Coherence Error Detection for Narrative Summarization",
author = "Goyal, Tanya and
Li, Junyi Jessy and
Durrett, Greg",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.29",
pages = "444--463"
}