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Narrative Time

First timeline-based annotation framework that achieves full coverage of all possible TLINKS.

Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.

Repository structure:

  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus
    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format

Conversion to TML format

Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:

python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1

nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.

The tool has several optional arguments that allow the user to customize the conversion process:

  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.

Citation

@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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Readme
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4 watching
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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MIT license
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4 watching
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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4 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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Resources
Readme
MIT license
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Stars
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Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
Custom properties
Stars
6 stars
Watchers
4 watching
Forks
0 forks
Report repository
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Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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Narrative Time
First timeline-based annotation framework that achieves full coverage of all possible TLINKS.
Companion paper: NarrativeTime: Dense Temporal Annotation on a Timeline.
Repository structure:
  • annotationTool: contains the annotation tool. Just open AnnotationTool.html in your browser.
  • corpus: contains NarrativeTime-annotated TimeBank corpus

    • nt_format: output of the annotation tool in NarrativeTime format. If the file ends with _tml, it has extra TimeBank metadata.
    • nt_converted_to_tml: NarrativeTime format converted to TML format using utils/nt2tml.py
  • narrative_time: contains the NarrativeTime package, it is a Python package that can be installed using pip install -e .. It contains useful functions to work with NarrativeTime format.
  • notebooks: contains Jupyter notebooks with EDA, agreement computation and modeling
  • utils: contains conversion script and a script to add metadata to NarrativeTime format
Conversion to TML format
Annotation tool output can be converted to TML format using utils/nt2tml.py script. Usage example:
python narrative_time/nt2tml.py \
--input_file corpus/timebank/nt_format/tbd_a1_tml.jsonl \
--output_dir corpus/timeml_converted/a1
nt2tml.py is a command line tool that converts data in the NarrativeTime format (a jsonl file) to the TimeML format (a set of xml files) and saves the xml files to the specified output directory.
The tool has several optional arguments that allow the user to customize the conversion process:
  • --verbocity: Controls the level of output that the tool prints. With a value of 0, no output is printed. With a value of 1, only the final results are printed. With a value of 2, all intermediate steps are printed as well.
  • --add_narrative_time_info: If this flag is present, the tool will add additional NarrativeTime tags to the output xml files. This can be useful for debugging or for making the xml files more readable. This flag does not affect tlinks, only the NarrativeTime tags.
  • --do_not_use_global_eiid: If this flag is present, the tool will always generate new eiids (event instance IDs) starting from 0, rather than using a global counter. This can be useful for testing.
Citation
@misc{rogers2022narrativetime,
title={NarrativeTime: Dense Temporal Annotation on a Timeline},
author={Anna Rogers and Marzena Karpinska and Ankita Gupta and Vladislav Lialin and Gregory Smelkov and Anna Rumshisky},
year={2022},
eprint={1908.11443},
archivePrefix={arXiv},
primaryClass={cs.CL}
}

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