Challenge: Unlike previous Wiktionary extractions, the new extractor, Wiktextract, fully interprets and expands templates and Lua modules in Wiktionaries.
Approach: They propose a machine-readable structured version of Wiktionary that interprets and expands templates and Lua modules.
Outcome: The extracted data is multilingual and includes lemmas, inflected forms, translations, etymology, usage examples, pronunciations, and various morphological, syntactic, semantic, topical, and dialectal annotations.

Similar Papers

ENGLAWI: From Human- to Machine-Readable Wiktionary (2020.lrec-1)

Copied to clipboard

Challenge: ENGLAWI is a structured and normalized version of the English Wiktionary encoded into a workable XML format.
Approach: They introduce ENGLAWI, a large, versatile, XML-encoded machine-readable dictionary extracted from Wiktionary.
Outcome: The proposed lexicographic word embeddings are based on the ENGLAWI definitions and are available for download and are supplied with G-PeTo scripts.
Wiktionary Normalization of Translations and Morphological Information (2020.coling-main)

Copied to clipboard

Challenge: We extend the Yawipa Wiktionary Parser to extract and normalize translations from etymology glosses and morphological form-of relations.
Approach: They extend Yawipa to extract and normalize translations from etymology glosses . they propose a method to identify typos in translation annotations based on extracted morphological data .
Outcome: The proposed method improves on a standard attention baseline by using copy attention.
Wikinflection Corpus: A (Better) Multilingual, Morpheme-Annotated Inflectional Corpus (2020.lrec-1)

Copied to clipboard

Challenge: Inflectional corpora with annotated morpheme boundaries are scarce in the NLP community . a generated, multilingual inflectional lexicon with morphological features is not as good as UniMorph's .
Approach: They evaluate a multilingual inflectional corpus with morpheme boundaries from the English Wiktionary and the UniMorph project's inflection corpus.
Outcome: The generated Wikinflection corpus is not as good as UniMorph's, but extracts significant amount of words from the intersection of the two corpora.
Using Wiktionary to Create Specialized Lexical Resources and Datasets (2022.lrec-1)

Copied to clipboard

Challenge: Using Wiktionary data to build specialized lexical datasets can be used for evaluating or improving NLP tasks, like Word Sense Disambiguation (WSD), Word-in-Context challenges (WiC), or Machine Translation (MT).
Approach: They propose to use Wiktionary data to create specialized lexical datasets that can be used for evaluating or improving NLP tasks.
Outcome: The proposed datasets can be used to improve and/or evaluate NLP tasks, like Word Sense Disambiguation (WSD), Word-in-Context challenges (WiC), or Sense Linking (SL), or machine translation (MT).
Massively Multilingual Pronunciation Modeling with WikiPron (2020.lrec-1)

Copied to clipboard

Challenge: WikiPron is an open-source command-line tool for extracting pronunciation data from Wiktionary . the tool generates a database of 1.7 million pronunciations from 165 languages .
Approach: They propose a command-line tool for extracting pronunciation data from Wiktionary . they use it to generate a database of 1.7 million pronunciations from 165 languages .
Outcome: The proposed software generates a database of pronunciations for 165 languages . the proposed model is then validated by a grapheme-to-phoneme model .
Knowledge Extraction From Texts Based on Wikidata (2022.naacl-industry)

Copied to clipboard

Challenge: Existing knowledge extraction pipelines for English are not suitable for enterprise use.
Approach: They propose a knowledge extraction pipeline for English which can be further used for building an entreprise-specific knowledge base.
Outcome: The proposed pipeline can be used to build an entreprise-specific knowledge base.
ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images (2026.eacl-long)

Copied to clipboard

Challenge: Existing models for structured information extraction are limited by narrow entity ontologies, simple queries, or homogeneous document types.
Approach: They propose a benchmark dataset for structured Information Extraction (IE) from document images . they analyze open and closed VLMs on this benchmark .
Outcome: The proposed model can perform fine-grained structured extraction across document types and schemas.
The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

Copied to clipboard

Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
Approach: They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful.
Outcome: The proposed corpus is searchable through a couple of well-established corpus infrastructures.
Computational Etymology and Word Emergence (2020.lrec-1)

Copied to clipboard

Challenge: etymology is the study of words' origins.
Approach: They develop an extensible Wiktionary parser that predicts the etymology of a word across the full range of ethymological types and languages in Wiktionaries.
Outcome: The proposed parser predicts the etymology of a word across the full range of ethymologies and languages in Wiktionary, and shows the application of tymatics in modeling this phenomenon.
A Gold Standard for Multilingual Automatic Term Extraction from Comparable Corpora: Term Structure and Translation Equivalents (L18-1)

Copied to clipboard

Challenge: Terms are notoriously difficult to identify, both automatically and manually.
Approach: They propose a method to annotate terms manually from a comparable corpus . they show that the gold standard provides a tool for evaluation and a rich source of information .
Outcome: The proposed method provides a tool for evaluation and rich source of information about terms.

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