Papers with building process

4 papers
Going “Deeper”: Structured Sememe Prediction via Transformer with Tree Attention (2022.findings-acl)

Copied to clipboard

Challenge: Existing studies ignore hierarchical structures of sememes in sememe-based semantic description systems.
Approach: They propose a structured sememe prediction problem to predict a sememes tree with hierarchical structures rather than a set of sememas.
Outcome: The proposed model outperforms baseline models and shows its effectiveness . it predicts a sememe tree with hierarchical structures rather than a set of sememes .
WordNet-Shp: Towards the Building of a Lexical Database for a Peruvian Minority Language (L18-1)

Copied to clipboard

Challenge: WordNet-like resources are lexical databases with highly relevance information and data that could be exploited in more complex computational linguistics research and applications.
Approach: They propose to build a WordNet database for a low-resourced and indigenous language in Peru . they propose to use word2vec similarity to compare definition glosses in a dictionary with the content of a Spanish WordNet .
Outcome: The proposed database is based on a bilingual dictionary written in Spanish and an automatic evaluation process using a manually annotated Gold Standard in Shipibo-Koniba.
TArC: Incrementally and Semi-Automatically Collecting a Tunisian Arabish Corpus (2020.lrec-1)

Copied to clipboard

Challenge: Arabish is a spontaneous coding of Arabic dialects in Latin characters and "arithmographs" this code-system was developed by Arabic-speaking users of social media . little research has been dedicated to Tunisian Arabish (TA)
Approach: They describe the constitution process of the first morpho-syntactically annotated Tunisian Arabish Corpus . they describe preliminary work on the TArC semi-automatic construction process .
Outcome: The first morpho-syntactically annotated Tunisian Arabish corpus (TArC) was developed by arab-speaking users of social media . the code-system will be a useful support for different types of analyses, computational and linguistic, as well as for NLP tools training.
French Tweet Corpus for Automatic Stance Detection (2020.lrec-1)

Copied to clipboard

Challenge: a new corpus of tweets is being developed for automatic stance detection of fake news . the task involves determining the attitude expressed in a text toward a target . this is a difficult task to overcome as discussions about fake news are controversial .
Approach: They propose to build a human-annotated corpus for automatic stance detection of tweets in french . they propose to use four classes broadly adopted by the community for annotation .
Outcome: The proposed corpus is the first freely available stance annotated tweet corpus in the french language.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations