UDMorph: Morphosyntactically Tagged UD Corpora (2024.lrec-main)

Copied to clipboard

Challenge: a range of different problems exist in using annotated corpus data and training data . linguistic annotations are only available for a limited amount of typically major languages .
Approach: a new corpus creation environment provides annotated corpus data for additional languages . a range of different problems exist in using these new tools and training data .
Outcome: a new tool provides an infrastructure for annotated corpus data that follows UD guidelines . a GUI interface to a growing collection taggers with a CoNLL-U output is available for 150 languages .

Similar Papers

UCxn: Typologically-Informed Annotation of Constructions Atop Universal Dependencies (2024.lrec-main)

Copied to clipboard

Challenge: Grammatical constructions that convey meaning through a particular combination of several morphosyntactic elements are not labeled holistically.
Approach: They propose to augment UD annotations with a ‘UCxn’ annotation layer for such meaning-bearing grammatical constructions and to approach this in a typologically informed way so that morphosyntactic strategies can be compared across languages.
Outcome: The proposed annotation layer could be used to annotate meaning-bearing constructions across languages and to compare them across languages.
Universal Dependencies for Ainu (L18-1)

Copied to clipboard

Challenge: a task is underway to create a dependency tree bank for the Ainu language in the scheme of Universal Dependencies (UD).
Approach: They propose to create a dependency tree bank for the Ainu language in the scheme of Universal Dependencies (UD) their mini-lexicon is encoded under the W3C OntoLex specification with UD and UniMorph features with the system-friendly JSON-LD format and is bearable to future extensions.
Outcome: The proposed tree bank contains 10,000 word tokens and is small enough to be used as a base annotation for the next step.
Spoken Language Treebanks in Universal Dependencies: an Overview (2022.lrec-1)

Copied to clipboard

Challenge: spoken language treebanks have divergent annotation schemes limiting cross-resource explorations . many spoken language trees have no written form, but many of the world languages have no spoken form at all.
Approach: They propose to use the Universal Dependencies annotation scheme to annotate spoken language treebanks using a morphosyntactic annotation scheme.
Outcome: The proposed treebanks differ significantly with respect to the inventory and format of transcribed phenomena and the principles adopted in their morphosyntactic annotation.
CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing (L18-1)

Copied to clipboard

Challenge: Using the universal dependencies framework, we address the need for a universal representation of morphological analysis that can capture alternative morphology of surface tokens and is compatible with the segmentation and morphologic annotation guidelines prescribed for UD treebanks.
Approach: They propose a new annotation format for word lattices that represent morphological analyses and a resource that obeys this format for a range of typologically different languages.
Outcome: The proposed model can capture alternative morphological analyses of surface tokens and is compatible with the segmentation and morphology guidelines prescribed for UD treebanks.
CorefUD 1.0: Coreference Meets Universal Dependencies (2022.lrec-1)

Copied to clipboard

Challenge: Recent advances in standardization for annotated language resources have led to successful large scale efforts, such as the Universal Dependencies (UD) project for multilingual syntactically annotized data.
Approach: They propose a multilingual collection of corpora and a standardized format for coreference resolution compatible with morphosyntactic annotations in the UD framework.
Outcome: The proposed framework is compatible with morphosyntactic annotations and includes facilities for related tasks such as named entity recognition.
UniMorph 4.0: Universal Morphology (2022.lrec-1)

Copied to clipboard

Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Abbott Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud’hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova
Challenge: The Universal Morphology project provides broad-coverage instantiated morphological inflection tables for hundreds of diverse languages.
Approach: They propose a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Outcome: The proposed schema has added 66 new languages, including 24 endangered languages.
CoBaLD Annotation: The Enrichment of the Enhanced Universal Dependencies with the Semantical Pattern (2024.lrec-main)

Copied to clipboard

Challenge: a new annotation format is developed to support morphological, syntactic and semantic markup . the format is based on the Compreno semantics, which is a simplified version of the standard .
Approach: They propose a new annotation format that combines Enhanced UD morphosyntax and Compreno semantic pattern to enrich the UD annotation with word meanings and labels for semantic relations between words.
Outcome: The proposed format is aimed at morphological, syntactic and especially semantic markup . the proposed format reduces the number of semantic fields denoting lexical meanings .
A multilingual collection of CoNLL-U-compatible morphological lexicons (L18-1)

Copied to clipboard

Challenge: Existing morphological lexicons are limited in scope and are not universally accepted . morphology lexical information is encoded into morphologists or gathered in lexiconics .
Approach: They propose a multilingual collection of morphological lexicons that follow the Universal Dependencies initiative.
Outcome: The proposed collection of 53 morphological lexicons covers 38 languages . they have been shown to improve part-of-speech tagging and parsing accuracy .
Universal Dependencies Version 2 for Japanese (L18-1)

Copied to clipboard

Challenge: UD Japanese resources are built on automatic conversion from several treebanks.
Approach: They propose to port the word delimitation, POS, and syntactic relations of existing treebanks to UD Japanese . they discuss the issues of the UD scheme found through porting of the Japanese language .
Outcome: The proposed UD Japanese resources are based on automatic conversion from treebanks.
UniMorph 3.0: Universal Morphology (2020.lrec-1)

Copied to clipboard

Challenge: Explicit modeling of morphology has demonstrable benefits for language modeling, speech recognition, word embedding and keyword search.
Approach: They propose a language-independent feature schema for rich morphological annotation and a type-level resource for annotated data in diverse languages.
Outcome: The proposed schema has been improved to make it more complete and correct, and adds 66 new languages and parts of speech for 12 languages.

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