| Challenge: | In this paper, we present the building of a dependency treebank for Vietnamese . |
| Approach: | They propose to build a Vietnamese dependency treebank using automatic taggers and automatic tagging. |
| Outcome: | The proposed treebank is a useful resource for Vietnamese language processing. |
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Building Universal Dependency Treebanks in Korean (L18-1)
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| Challenge: | Several treebanks were introduced for Korean, all of which comprised annotation of morphemes and phrase structure trees, each following its own set of guidelines. |
| Approach: | They propose to use Korean treebanks as dependency trees and to analyze their performance using morpheme-level annotations. |
| Outcome: | The Korean portion of the Google UD Treebank, the Penn Korean Treebank and the KAIST Treebank are re-tokenized and assessed for errors. |
A Gold Standard Dependency Treebank for Turkish (2020.lrec-1)
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| Challenge: | Currently, Turkish treebanks are limited due to the limited number of annotated sentences in the domains of Wikipedia and ITU Web Treebanks. |
| Approach: | They propose to annotate Turkish web and Wikipedia sentences for segmentation, morphology, part-of-speech and dependency relations using tagsets and a Wikipedia section. |
| Outcome: | The proposed treebank is the largest publicly available morpho-syntactic treebank in terms of word count and has a dedicated Wikipedia section. |
Parser Training with Heterogeneous Treebanks (P18-2)
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| Challenge: | In the 2017 CoNLL Shared Task on Universal Dependency Parsing, 25 languages have more than one treebank . many teams did not take advantage of the multiple treebanks, however, and trained one model per treebank instead of one model for each language. |
| Approach: | They propose a method to make the most of heterogeneous treebanks when training a monolingual parser. |
| Outcome: | The proposed method improves on training with multiple treebanks for a single language. |
Universal Dependencies for Punjabi (2022.lrec-1)
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| Challenge: | UD is a community project that maintains a standard scheme for the annotation of grammar in a cross-lingually consistent manner. |
| Approach: | They propose a Universal Dependencies treebank for Punjabi written in the Gurmukhi script and discuss corpus design and linguistic phenomena encountered in annotation. |
| Outcome: | The proposed treebank covers a variety of genres and has been annotated for POS tags, dependency relations, and graph-based Enhanced Dependencies. |
Development of a Multilingual CCG Treebank via Universal Dependencies Conversion (2022.lrec-1)
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| Challenge: | Combinatory Categorial Grammar (CCG) is a lexicalized grammar formalism that can capture both syntactic and semantic information. |
| Approach: | They propose an algorithm to convert UD treebanks to CCG treebank and propose future extensions. |
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Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection (2020.lrec-1)
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Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Jan Hajič, Christopher D. Manning, Sampo Pyysalo, Sebastian Schuster, Francis Tyers, Daniel Zeman
| Challenge: | Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages. |
| Approach: | They describe version 2 of the universal guidelines and discuss major changes from UD v1 to UD 2 . they propose a morphological layer, a syntactic layer and a word segmentation layer . |
| Outcome: | The proposed treebanks are available for 90 languages and have been updated to meet the needs of multilingual parsers and researchers. |
The Persian Dependency Treebank Made Universal (2022.lrec-1)
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| Challenge: | Existing universal dependency treebanks are lacking sufficient annotated data. |
| Approach: | They propose a method for converting Persian Dependency Treebank to Universal Dependencies using an automatic method. |
| Outcome: | The proposed method is more compatible with Universal Dependencies than the Uppsala Persian Universal Dependency Treebank. |
Establishing a New State-of-the-Art for French Named Entity Recognition (2020.lrec-1)
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| Challenge: | Named entity recognition (NER) is a task consisting in identifying text spans that denote named entities such as person, location and organization names. |
| Approach: | They manually annotated the French TreeBank with information related to named entities . they sketch the underlying annotation guidelines and provide a few figures about the annotations . |
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Treebank Embedding Vectors for Out-of-Domain Dependency Parsing (2020.acl-main)
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| Challenge: | a recent advance in monolingual dependency parsing is the idea of a treebank embedding vector . this allows the model to prefer training data from one treebank over another at test time . |
| Approach: | They propose a method to predict a treebank vector for sentences that do not come from a particular treebank . they also explore what happens when they move away from predefined treebank embedding vectors . |
| Outcome: | The proposed method can predict treebank vectors for sentences that do not come from a treebank used in training with sufficient accuracy for nine out of ten languages. |
Cheating a Parser to Death: Data-driven Cross-Treebank Annotation Transfer (L18-1)
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| Challenge: | Using annotated corpus for linguistic purposes is no longer justified . hand-crafted syntactic resources such as grammars and lexicons can be used as sources of features to guide data driven systems. |
| Approach: | They propose an efficient method for transferring annotations between two different treebanks of the same language. |
| Outcome: | The proposed method is based on the Universal Dependency annotation scheme and was evaluated on the gold standard (94.75% of LAS, 99.40% UAS on the test set). |