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Part 1: Document Description
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Citation |
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Title: |
CoCo-Ex |
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Identification Number: |
doi:10.11588/data/K8MCIW |
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Distributor: |
heiDATA |
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Date of Distribution: |
2024-02-26 |
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Version: |
1 |
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Bibliographic Citation: |
Becker, Maria, 2024, "CoCo-Ex", https://doi.org/10.11588/data/K8MCIW, heiDATA, V1 |
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Citation |
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Title: |
CoCo-Ex |
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Identification Number: |
doi:10.11588/data/K8MCIW |
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Authoring Entity: |
Becker, Maria (Heidelberg, University, Department of Computational Linguistics) |
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Grant Number: |
SPP-1999 |
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Grant Number: |
FR1707/-4-1 |
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Grant Number: |
SAS-2015-IDS-LWC |
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Distributor: |
heiDATA |
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Access Authority: |
Becker, Maria |
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Holdings Information: |
https://doi.org/10.11588/data/K8MCIW |
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Study Scope |
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Keywords: |
Arts and Humanities, Computer and Information Science |
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Abstract: |
CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph. |
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Notes: |
Source Code also available at GitHub: <a href="https://github.com/Heidelberg-NLP/CoCo-Ex">https://github.com/Heidelberg-NLP/CoCo-Ex</a>. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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cn_dict2.p.zip |
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Notes: |
application/zip |
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CoCo-Ex_Annotation_Manual.pdf |
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Notes: |
application/pdf |
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CoCo-Ex_entity_extraction.py |
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text/x-python |
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CoCo-Ex_overhead_filter.py |
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Notes: |
text/x-python |
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cos_sim.py |
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Notes: |
text/x-python |
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penn_to_universal_tagset_mapping.txt |
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Notes: |
text/plain |
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phrases.txt |
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Notes: |
text/plain |
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phrases_simplification_mapping.txt |
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text/plain |
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README.md |
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Notes: |
text/markdown |